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diff --git a/api/examples/heart_failure_report_periodic.html b/api/examples/heart_failure_report_periodic.html index fc7293dcd..0024da487 100644 --- a/api/examples/heart_failure_report_periodic.html +++ b/api/examples/heart_failure_report_periodic.html @@ -1167,7 +1167,7 @@

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diff --git a/api/examples/metrics.ipynb b/api/examples/metrics.ipynb
index e3ea8a39b..8e373a082 100644
--- a/api/examples/metrics.ipynb
+++ b/api/examples/metrics.ipynb
@@ -14,10 +14,10 @@
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-     "shell.execute_reply": "2024-06-23T21:30:55.880068Z"
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@@ -43,10 +43,10 @@
    "execution_count": 2,
    "metadata": {
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@@ -69,10 +69,10 @@
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@@ -536,10 +536,10 @@
    "execution_count": 4,
    "metadata": {
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@@ -582,10 +582,10 @@
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-     "shell.execute_reply": "2024-06-23T21:30:56.897769Z"
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@@ -618,10 +618,10 @@
    "execution_count": 6,
    "metadata": {
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-     "shell.execute_reply": "2024-06-23T21:30:56.947611Z"
+     "iopub.execute_input": "2024-06-24T17:10:07.829248Z",
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@@ -667,10 +667,10 @@
    "execution_count": 7,
    "metadata": {
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-     "shell.execute_reply": "2024-06-23T21:30:57.010240Z"
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@@ -711,10 +711,10 @@
    "execution_count": 8,
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@@ -767,10 +767,10 @@
    "execution_count": 9,
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@@ -805,10 +805,10 @@
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@@ -824,17 +824,17 @@
    "execution_count": 11,
    "metadata": {
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+     "shell.execute_reply": "2024-06-24T17:10:08.526717Z"
     }
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    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fc2f3b9c797644efa0c667de6412e34f",
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@@ -848,7 +848,7 @@
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@@ -862,7 +862,7 @@
     {
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@@ -876,7 +876,7 @@
     {
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@@ -891,7 +891,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/mnt/data/actions_runners/cyclops-actions-runner-2/_work/cyclops/cyclops/cyclops/evaluate/metrics/experimental/functional/roc.py:74: UserWarning:\n",
+      "/mnt/data/actions_runners/cyclops-actions-runner-1/_work/cyclops/cyclops/cyclops/evaluate/metrics/experimental/functional/roc.py:74: UserWarning:\n",
       "\n",
       "No negative samples in targets false positive value should be meaningless. Returning an array of 0s instead.\n",
       "\n"
@@ -900,7 +900,7 @@
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@@ -914,7 +914,7 @@
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@@ -950,10 +950,10 @@
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-     "shell.execute_reply": "2024-06-23T21:30:58.550332Z"
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@@ -1900,9 +1900,9 @@
        }
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       "text/html": [
-       "
                            
            

+
-
+
-
+
[27]:
@@ -1981,9 +1981,9 @@ 
Logging metrics and results to report
-
diff --git a/api/examples/report.ipynb b/api/examples/report.ipynb index 92d979e8b..9c2f07a36 100644 --- a/api/examples/report.ipynb +++ b/api/examples/report.ipynb @@ -5,10 +5,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:31:13.143377Z", - "iopub.status.busy": "2024-06-23T21:31:13.142205Z", - "iopub.status.idle": "2024-06-23T21:31:25.636063Z", - "shell.execute_reply": "2024-06-23T21:31:25.634051Z" + "iopub.execute_input": "2024-06-24T17:10:25.059237Z", + "iopub.status.busy": "2024-06-24T17:10:25.058309Z", + "iopub.status.idle": "2024-06-24T17:10:37.726012Z", + "shell.execute_reply": "2024-06-24T17:10:37.723565Z" } }, "outputs": [], @@ -58,10 +58,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:31:25.644813Z", - "iopub.status.busy": "2024-06-23T21:31:25.643430Z", - "iopub.status.idle": "2024-06-23T21:31:25.652462Z", - "shell.execute_reply": "2024-06-23T21:31:25.650673Z" + "iopub.execute_input": "2024-06-24T17:10:37.735485Z", + "iopub.status.busy": "2024-06-24T17:10:37.734127Z", + "iopub.status.idle": "2024-06-24T17:10:37.743108Z", + "shell.execute_reply": "2024-06-24T17:10:37.741504Z" } }, "outputs": [], @@ -74,10 +74,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:31:25.659069Z", - "iopub.status.busy": "2024-06-23T21:31:25.658374Z", - "iopub.status.idle": "2024-06-23T21:31:25.667136Z", - "shell.execute_reply": "2024-06-23T21:31:25.665320Z" + "iopub.execute_input": "2024-06-24T17:10:37.752613Z", + "iopub.status.busy": "2024-06-24T17:10:37.751208Z", + "iopub.status.idle": "2024-06-24T17:10:37.765037Z", + "shell.execute_reply": "2024-06-24T17:10:37.763243Z" } }, "outputs": [], @@ -100,10 +100,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:31:25.674906Z", - "iopub.status.busy": "2024-06-23T21:31:25.673466Z", - "iopub.status.idle": "2024-06-23T21:31:26.787496Z", - "shell.execute_reply": "2024-06-23T21:31:26.785733Z" + "iopub.execute_input": "2024-06-24T17:10:37.772059Z", + "iopub.status.busy": "2024-06-24T17:10:37.771146Z", + "iopub.status.idle": "2024-06-24T17:10:38.433256Z", + "shell.execute_reply": "2024-06-24T17:10:38.431588Z" } }, "outputs": [], @@ -122,10 +122,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:31:26.795561Z", - "iopub.status.busy": "2024-06-23T21:31:26.793922Z", - "iopub.status.idle": "2024-06-23T21:31:26.865040Z", - "shell.execute_reply": "2024-06-23T21:31:26.863554Z" + "iopub.execute_input": "2024-06-24T17:10:38.440688Z", + "iopub.status.busy": "2024-06-24T17:10:38.439677Z", + "iopub.status.idle": "2024-06-24T17:10:38.924236Z", + "shell.execute_reply": "2024-06-24T17:10:38.922404Z" } }, "outputs": [ @@ -275,10 +275,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:31:26.872341Z", - "iopub.status.busy": "2024-06-23T21:31:26.870828Z", - "iopub.status.idle": "2024-06-23T21:31:26.938742Z", - "shell.execute_reply": "2024-06-23T21:31:26.936992Z" + "iopub.execute_input": "2024-06-24T17:10:38.931305Z", + "iopub.status.busy": "2024-06-24T17:10:38.930707Z", + "iopub.status.idle": "2024-06-24T17:10:39.001249Z", + "shell.execute_reply": "2024-06-24T17:10:38.999464Z" } }, "outputs": [ @@ -420,10 +420,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:31:26.948699Z", - "iopub.status.busy": "2024-06-23T21:31:26.947988Z", - "iopub.status.idle": "2024-06-23T21:31:27.718600Z", - "shell.execute_reply": "2024-06-23T21:31:27.716094Z" + "iopub.execute_input": "2024-06-24T17:10:39.008716Z", + "iopub.status.busy": "2024-06-24T17:10:39.007473Z", + "iopub.status.idle": "2024-06-24T17:10:39.715008Z", + "shell.execute_reply": "2024-06-24T17:10:39.709308Z" } }, "outputs": [ @@ -2230,9 +2230,9 @@ } }, "text/html": [ - "
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@@ -1276,7 +1269,7 @@

Training 

-2024-06-23 17:50:07,717 INFO cyclops.models.wrappers.sk_model - Best scale_pos_weight: 9
+2024-06-24 13:23:19,526 INFO cyclops.models.wrappers.sk_model - Best scale_pos_weight: 9
@@ -1284,7 +1277,7 @@

Training 

-2024-06-23 17:50:07,722 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
+2024-06-24 13:23:19,534 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 10
@@ -1292,7 +1285,7 @@

Training 

-2024-06-23 17:50:07,724 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 500
+2024-06-24 13:23:19,536 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 250
@@ -1300,7 +1293,7 @@

Training 

-2024-06-23 17:50:07,725 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
+2024-06-24 13:23:19,537 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
@@ -1308,7 +1301,7 @@

Training 

-2024-06-23 17:50:07,726 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
+2024-06-24 13:23:19,538 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
@@ -1316,7 +1309,7 @@

Training 

-2024-06-23 17:50:07,728 INFO cyclops.models.wrappers.sk_model - Best gamma: 0
+2024-06-24 13:23:19,539 INFO cyclops.models.wrappers.sk_model - Best gamma: 2
@@ -1324,7 +1317,7 @@

Training 

-2024-06-23 17:50:07,729 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.7
+2024-06-24 13:23:19,540 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.7
@@ -1740,22 +1733,22 @@

Training colsample_bylevel=None, colsample_bynode=None, colsample_bytree=0.7, early_stopping_rounds=None, enable_categorical=False, eval_metric='logloss', - feature_types=None, gamma=0, gpu_id=None, grow_policy=None, + feature_types=None, gamma=2, gpu_id=None, grow_policy=None, importance_type=None, interaction_constraints=None, learning_rate=0.1, max_bin=None, max_cat_threshold=None, max_cat_to_onehot=None, max_delta_step=None, max_depth=5, max_leaves=None, min_child_weight=3, missing=nan, - monotone_constraints=None, n_estimators=500, n_jobs=None, + monotone_constraints=None, n_estimators=250, n_jobs=None, num_parallel_tree=None, predictor=None, random_state=123, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

@@ -1772,7 +1765,7 @@

Training 

-{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.7, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 0, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 500, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': 9, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}
+{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.7, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 2, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 250, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 10, 'sampling_method': None, 'scale_pos_weight': 9, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}

Log the model parameters to the report.

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Prediction
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Evaluation
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Evaluation
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Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -2191,9 +2184,9 @@

Evaluation
-

diff --git a/api/tutorials/diabetes_130/readmission_prediction.ipynb b/api/tutorials/diabetes_130/readmission_prediction.ipynb index 6c5c4326c..6cd694c2b 100644 --- a/api/tutorials/diabetes_130/readmission_prediction.ipynb +++ b/api/tutorials/diabetes_130/readmission_prediction.ipynb @@ -23,10 +23,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:12.632069Z", - "iopub.status.busy": "2024-06-23T21:32:12.631488Z", - "iopub.status.idle": "2024-06-23T21:32:37.815904Z", - "shell.execute_reply": "2024-06-23T21:32:37.813621Z" + "iopub.execute_input": "2024-06-24T17:11:22.493745Z", + "iopub.status.busy": "2024-06-24T17:11:22.492182Z", + "iopub.status.idle": "2024-06-24T17:11:46.749799Z", + "shell.execute_reply": "2024-06-24T17:11:46.747481Z" }, "tags": [] }, @@ -35,200 +35,194 @@ "name": "stdout", "output_type": "stream", "text": [ - "Requirement already satisfied: pycyclops in /mnt/data/actions_runners/cyclops-actions-runner-2/_work/cyclops/cyclops/.venv/lib/python3.10/site-packages (0.2.9)\r\n" + "Requirement already satisfied: pycyclops in /mnt/data/actions_runners/cyclops-actions-runner-1/_work/cyclops/cyclops/.venv/lib/python3.10/site-packages (0.2.9)\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - 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"iopub.execute_input": "2024-06-23T21:32:37.842736Z", - "iopub.status.busy": "2024-06-23T21:32:37.841788Z", - "iopub.status.idle": "2024-06-23T21:32:50.840407Z", - "shell.execute_reply": "2024-06-23T21:32:50.838757Z" + "iopub.execute_input": "2024-06-24T17:11:46.758521Z", + "iopub.status.busy": "2024-06-24T17:11:46.757500Z", + "iopub.status.idle": "2024-06-24T17:11:59.830387Z", + "shell.execute_reply": "2024-06-24T17:11:59.828691Z" }, "tags": [] }, @@ -318,10 +312,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:50.849958Z", - "iopub.status.busy": "2024-06-23T21:32:50.847939Z", - "iopub.status.idle": "2024-06-23T21:32:50.856649Z", - "shell.execute_reply": "2024-06-23T21:32:50.855128Z" + "iopub.execute_input": "2024-06-24T17:11:59.838347Z", + "iopub.status.busy": "2024-06-24T17:11:59.836803Z", + "iopub.status.idle": "2024-06-24T17:11:59.844961Z", + "shell.execute_reply": "2024-06-24T17:11:59.843809Z" } }, "outputs": [], @@ -341,10 +335,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:50.863797Z", - "iopub.status.busy": "2024-06-23T21:32:50.862887Z", - "iopub.status.idle": "2024-06-23T21:32:50.876465Z", - "shell.execute_reply": "2024-06-23T21:32:50.874696Z" + "iopub.execute_input": "2024-06-24T17:11:59.852031Z", + "iopub.status.busy": "2024-06-24T17:11:59.850777Z", + "iopub.status.idle": "2024-06-24T17:11:59.859162Z", + "shell.execute_reply": "2024-06-24T17:11:59.857417Z" }, "tags": [] }, @@ -368,10 +362,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:50.884208Z", - "iopub.status.busy": "2024-06-23T21:32:50.882653Z", - "iopub.status.idle": "2024-06-23T21:32:55.237904Z", - "shell.execute_reply": "2024-06-23T21:32:55.235806Z" + "iopub.execute_input": "2024-06-24T17:11:59.864632Z", + "iopub.status.busy": "2024-06-24T17:11:59.863976Z", + "iopub.status.idle": "2024-06-24T17:12:04.414535Z", + "shell.execute_reply": "2024-06-24T17:12:04.412776Z" }, "tags": [] }, @@ -389,10 +383,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:55.245735Z", - "iopub.status.busy": "2024-06-23T21:32:55.245129Z", - "iopub.status.idle": "2024-06-23T21:32:55.278209Z", - "shell.execute_reply": "2024-06-23T21:32:55.276573Z" + "iopub.execute_input": "2024-06-24T17:12:04.422957Z", + "iopub.status.busy": "2024-06-24T17:12:04.421430Z", + "iopub.status.idle": "2024-06-24T17:12:04.449057Z", + "shell.execute_reply": "2024-06-24T17:12:04.445020Z" }, "tags": [] }, @@ -451,10 +445,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:55.286997Z", - "iopub.status.busy": "2024-06-23T21:32:55.286015Z", - "iopub.status.idle": "2024-06-23T21:32:55.495898Z", - "shell.execute_reply": "2024-06-23T21:32:55.494365Z" + "iopub.execute_input": "2024-06-24T17:12:04.457479Z", + "iopub.status.busy": "2024-06-24T17:12:04.456138Z", + "iopub.status.idle": "2024-06-24T17:12:04.674060Z", + "shell.execute_reply": "2024-06-24T17:12:04.672138Z" }, "tags": [] }, @@ -499,10 +493,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:55.503562Z", - "iopub.status.busy": "2024-06-23T21:32:55.502012Z", - "iopub.status.idle": "2024-06-23T21:32:55.512282Z", - "shell.execute_reply": "2024-06-23T21:32:55.510904Z" + "iopub.execute_input": "2024-06-24T17:12:04.681932Z", + "iopub.status.busy": "2024-06-24T17:12:04.681188Z", + "iopub.status.idle": "2024-06-24T17:12:04.691639Z", + "shell.execute_reply": "2024-06-24T17:12:04.689933Z" } }, "outputs": [], @@ -522,10 +516,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:55.518786Z", - "iopub.status.busy": "2024-06-23T21:32:55.518075Z", - "iopub.status.idle": "2024-06-23T21:32:55.592454Z", - "shell.execute_reply": "2024-06-23T21:32:55.590904Z" + "iopub.execute_input": "2024-06-24T17:12:04.698265Z", + "iopub.status.busy": "2024-06-24T17:12:04.697593Z", + "iopub.status.idle": "2024-06-24T17:12:04.768279Z", + "shell.execute_reply": "2024-06-24T17:12:04.766745Z" }, "tags": [] }, @@ -550,10 +544,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:32:55.599884Z", - "iopub.status.busy": "2024-06-23T21:32:55.598901Z", - "iopub.status.idle": "2024-06-23T21:32:56.277885Z", - "shell.execute_reply": "2024-06-23T21:32:56.274470Z" + "iopub.execute_input": "2024-06-24T17:12:04.776041Z", + "iopub.status.busy": "2024-06-24T17:12:04.775217Z", + "iopub.status.idle": "2024-06-24T17:12:05.452981Z", + "shell.execute_reply": "2024-06-24T17:12:05.449408Z" }, "tags": [] }, @@ -2443,9 +2437,9 @@ } }, "text/html": [ - "
+
@@ -1026,7 +1026,7 @@

Training 
-2024-06-23 17:51:01,714 INFO cyclops.models.wrappers.sk_model - Best alpha: 0.001
+2024-06-24 13:24:13,523 INFO cyclops.models.wrappers.sk_model - Best alpha: 0.001
@@ -1034,7 +1034,7 @@

Training 

-2024-06-23 17:51:01,718 INFO cyclops.models.wrappers.sk_model - Best eta0: 0.01
+2024-06-24 13:24:13,530 INFO cyclops.models.wrappers.sk_model - Best eta0: 0.01
@@ -1042,7 +1042,7 @@

Training 

-2024-06-23 17:51:01,719 INFO cyclops.models.wrappers.sk_model - Best learning_rate: adaptive
+2024-06-24 13:24:13,534 INFO cyclops.models.wrappers.sk_model - Best learning_rate: adaptive
@@ -1516,7 +1516,7 @@

Prediction

-
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@@ -1635,67 +1635,67 @@

Evaluation
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[36]:
@@ -1726,37 +1726,37 @@ 
Evaluation
-
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Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -1873,9 +1873,9 @@

Evaluation
-

diff --git a/api/tutorials/kaggle/heart_failure_prediction.ipynb b/api/tutorials/kaggle/heart_failure_prediction.ipynb index b99264eea..6244cc797 100644 --- a/api/tutorials/kaggle/heart_failure_prediction.ipynb +++ b/api/tutorials/kaggle/heart_failure_prediction.ipynb @@ -21,10 +21,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:50:25.066792Z", - "iopub.status.busy": "2024-06-23T21:50:25.065744Z", - "iopub.status.idle": "2024-06-23T21:50:38.536197Z", - "shell.execute_reply": "2024-06-23T21:50:38.534063Z" + "iopub.execute_input": "2024-06-24T17:23:36.050321Z", + "iopub.status.busy": "2024-06-24T17:23:36.049384Z", + "iopub.status.idle": "2024-06-24T17:23:49.885367Z", + "shell.execute_reply": "2024-06-24T17:23:49.883195Z" }, "tags": [] }, @@ -90,10 +90,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:50:38.544949Z", - "iopub.status.busy": "2024-06-23T21:50:38.543338Z", - "iopub.status.idle": "2024-06-23T21:50:38.551911Z", - "shell.execute_reply": "2024-06-23T21:50:38.550164Z" + "iopub.execute_input": "2024-06-24T17:23:49.897308Z", + "iopub.status.busy": "2024-06-24T17:23:49.895022Z", + "iopub.status.idle": "2024-06-24T17:23:49.904244Z", + "shell.execute_reply": "2024-06-24T17:23:49.902489Z" } }, "outputs": [], @@ -113,10 +113,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:50:38.558779Z", - "iopub.status.busy": "2024-06-23T21:50:38.557943Z", - "iopub.status.idle": "2024-06-23T21:50:38.565826Z", - "shell.execute_reply": "2024-06-23T21:50:38.564121Z" + "iopub.execute_input": "2024-06-24T17:23:49.911282Z", + "iopub.status.busy": "2024-06-24T17:23:49.910190Z", + "iopub.status.idle": "2024-06-24T17:23:49.918120Z", + "shell.execute_reply": "2024-06-24T17:23:49.916441Z" }, "tags": [] }, @@ -142,10 +142,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:50:38.572422Z", - "iopub.status.busy": "2024-06-23T21:50:38.571596Z", - "iopub.status.idle": "2024-06-23T21:50:38.971476Z", - "shell.execute_reply": "2024-06-23T21:50:38.969542Z" + "iopub.execute_input": "2024-06-24T17:23:49.924931Z", + "iopub.status.busy": "2024-06-24T17:23:49.923923Z", + "iopub.status.idle": "2024-06-24T17:23:50.321921Z", + "shell.execute_reply": "2024-06-24T17:23:50.319898Z" }, "tags": [] }, @@ -165,10 +165,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:50:38.979490Z", - "iopub.status.busy": "2024-06-23T21:50:38.977930Z", - "iopub.status.idle": "2024-06-23T21:50:39.040513Z", - "shell.execute_reply": "2024-06-23T21:50:39.038701Z" + "iopub.execute_input": "2024-06-24T17:23:50.330529Z", + "iopub.status.busy": "2024-06-24T17:23:50.329107Z", + "iopub.status.idle": "2024-06-24T17:23:50.392574Z", + "shell.execute_reply": "2024-06-24T17:23:50.390865Z" }, "tags": [] }, @@ -177,7 +177,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 17:50:38,983 \u001b[1;37mINFO\u001b[0m cyclops.utils.file - Loading DataFrame from ./data/heart.csv\n" + "2024-06-24 13:23:50,333 \u001b[1;37mINFO\u001b[0m cyclops.utils.file - Loading DataFrame from ./data/heart.csv\n" ] }, { @@ -233,10 +233,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:50:39.048387Z", - "iopub.status.busy": "2024-06-23T21:50:39.046825Z", - "iopub.status.idle": "2024-06-23T21:50:39.773130Z", - "shell.execute_reply": "2024-06-23T21:50:39.771288Z" + "iopub.execute_input": "2024-06-24T17:23:50.400184Z", + "iopub.status.busy": "2024-06-24T17:23:50.398995Z", + "iopub.status.idle": "2024-06-24T17:23:51.134654Z", + "shell.execute_reply": "2024-06-24T17:23:51.132943Z" }, "tags": [] }, @@ -2044,9 +2044,9 @@ } }, "text/html": [ - "
+
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Graphics

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Graphics

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Graphics

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Graphics

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@@ -1886,7 +1886,7 @@

Version

- Date: 2024-06-23 + Date: 2024-06-24
@@ -2105,8 +2105,8 @@

Model Parameters

-

Tol

- 0.001 +

Penalty

+ l2
@@ -2114,8 +2114,8 @@

Tol

-

Fit_intercept

- True +

Class_weight

+ balanced
@@ -2123,8 +2123,8 @@

Fit_intercept

-

Alpha

- 0.001 +

Shuffle

+ True
@@ -2132,8 +2132,8 @@

Alpha

-

Validation_fraction

- 0.1 +

Alpha

+ 0.001
@@ -2141,8 +2141,8 @@

Validation_fraction

-

N_iter_no_change

- 5 +

Power_t

+ 0.5
@@ -2150,8 +2150,8 @@

N_iter_no_change

-

Power_t

- 0.5 +

Eta0

+ 0.01
@@ -2159,8 +2159,8 @@

Power_t

-

Shuffle

- True +

Tol

+ 0.001
@@ -2168,8 +2168,8 @@

Shuffle

-

Average

- False +

Epsilon

+ 0.1
@@ -2177,26 +2177,22 @@

Average

-

Penalty

- l2 +

Early_stopping

+ True
-
-

L1_ratio

- 0.15 -
-

Early_stopping

- True +

Random_state

+ 123
@@ -2204,8 +2200,8 @@

Early_stopping

-

Max_iter

- 1000 +

N_iter_no_change

+ 5
@@ -2213,8 +2209,8 @@

Max_iter

-

Learning_rate

- adaptive +

Validation_fraction

+ 0.1
@@ -2231,8 +2227,8 @@

Verbose

-

Epsilon

- 0.1 +

Warm_start

+ False
@@ -2240,22 +2236,26 @@

Epsilon

-

Loss

- log_loss +

Average

+ False
+
+

Fit_intercept

+ True +
-

Eta0

- 0.01 +

Learning_rate

+ adaptive
@@ -2263,8 +2263,8 @@

Eta0

-

Class_weight

- balanced +

Max_iter

+ 1000
@@ -2272,8 +2272,8 @@

Class_weight

-

Warm_start

- False +

L1_ratio

+ 0.15
@@ -2281,8 +2281,8 @@

Warm_start

-

Random_state

- 123 +

Loss

+ log_loss
diff --git a/api/tutorials/mimiciv/mortality_prediction.html b/api/tutorials/mimiciv/mortality_prediction.html index f83a2a2b4..c34957cf8 100644 --- a/api/tutorials/mimiciv/mortality_prediction.html +++ b/api/tutorials/mimiciv/mortality_prediction.html @@ -603,7 +603,7 @@

Compute mortality (labels) 
-2024-06-23 17:51:40,599 INFO cycquery.orm    - Database setup, ready to run queries!
+2024-06-24 13:24:52,532 INFO cycquery.orm    - Database setup, ready to run queries!
@@ -611,7 +611,7 @@

Compute mortality (labels) 
-2024-06-23 17:51:59,829 INFO cycquery.orm    - Query returned successfully!
+2024-06-24 13:25:13,433 INFO cycquery.orm    - Query returned successfully!

@@ -619,7 +619,7 @@

Compute mortality (labels) 
-2024-06-23 17:51:59,831 INFO cycquery.utils.profile - Finished executing function run_query in 16.893647 s
+2024-06-24 13:25:13,434 INFO cycquery.utils.profile - Finished executing function run_query in 18.668317 s

@@ -646,7 +646,7 @@

Compute mortality (labels) 
-2024-06-23 17:54:34,379 INFO cycquery.orm    - Query returned successfully!
+2024-06-24 13:26:19,751 INFO cycquery.orm    - Query returned successfully!

@@ -654,7 +654,7 @@

Compute mortality (labels) 
-2024-06-23 17:54:34,382 INFO cycquery.utils.profile - Finished executing function run_query in 151.679064 s
+2024-06-24 13:26:19,753 INFO cycquery.utils.profile - Finished executing function run_query in 63.297405 s

@@ -726,9 +726,9 @@

Drop NaNs based on the

-
+
@@ -1205,7 +1205,7 @@

Training 
-2024-06-23 18:01:51,540 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
+2024-06-24 13:43:39,411 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 1
@@ -1213,7 +1213,7 @@

Training 

-2024-06-23 18:01:51,561 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 500
+2024-06-24 13:43:39,415 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 100
@@ -1221,7 +1221,7 @@

Training 

-2024-06-23 18:01:51,564 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
+2024-06-24 13:43:39,416 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
@@ -1229,7 +1229,7 @@

Training 

-2024-06-23 18:01:51,566 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
+2024-06-24 13:43:39,417 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
@@ -1237,7 +1237,7 @@

Training 

-2024-06-23 18:01:51,568 INFO cyclops.models.wrappers.sk_model - Best gamma: 2
+2024-06-24 13:43:39,419 INFO cyclops.models.wrappers.sk_model - Best gamma: 0
@@ -1245,7 +1245,7 @@

Training 

-2024-06-23 18:01:51,569 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.7
+2024-06-24 13:43:39,420 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 1
@@ -1658,26 +1658,26 @@

Training background-color: var(--sklearn-color-fitted-level-3); } 
XGBClassifier(base_score=None, booster=None, callbacks=None,
-              colsample_bylevel=None, colsample_bynode=None,
-              colsample_bytree=0.7, early_stopping_rounds=None,
-              enable_categorical=False, eval_metric='logloss',
-              feature_types=None, gamma=2, gpu_id=None, grow_policy=None,
-              importance_type=None, interaction_constraints=None,
-              learning_rate=0.1, max_bin=None, max_cat_threshold=None,
-              max_cat_to_onehot=None, max_delta_step=None, max_depth=5,
-              max_leaves=None, min_child_weight=3, missing=nan,
-              monotone_constraints=None, n_estimators=500, n_jobs=None,
-              num_parallel_tree=None, predictor=None, random_state=123, ...)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

+ colsample_bylevel=None, colsample_bynode=None, colsample_bytree=1, + early_stopping_rounds=None, enable_categorical=False, + eval_metric='logloss', feature_types=None, gamma=0, gpu_id=None, + grow_policy=None, importance_type=None, + interaction_constraints=None, learning_rate=0.1, max_bin=None, + max_cat_threshold=None, max_cat_to_onehot=None, + max_delta_step=None, max_depth=5, max_leaves=None, + min_child_weight=3, missing=nan, monotone_constraints=None, + n_estimators=100, n_jobs=None, num_parallel_tree=None, + predictor=None, random_state=123, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org. 
[25]:
@@ -1693,7 +1693,7 @@ 
Training
 
-{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.7, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 2, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 500, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}
+{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 1, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 0, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 100, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 1, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}

Log the model parameters to the report.

@@ -1729,7 +1729,7 @@

Prediction

-
+
@@ -1854,91 +1854,91 @@

Evaluation

-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+

Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -2064,9 +2064,9 @@

Evaluation
-

diff --git a/api/tutorials/mimiciv/mortality_prediction.ipynb b/api/tutorials/mimiciv/mortality_prediction.ipynb index 7475727f0..a30a2e876 100644 --- a/api/tutorials/mimiciv/mortality_prediction.ipynb +++ b/api/tutorials/mimiciv/mortality_prediction.ipynb @@ -21,10 +21,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:51:24.560218Z", - "iopub.status.busy": "2024-06-23T21:51:24.558907Z", - "iopub.status.idle": "2024-06-23T21:51:38.074514Z", - "shell.execute_reply": "2024-06-23T21:51:38.072412Z" + "iopub.execute_input": "2024-06-24T17:24:35.821703Z", + "iopub.status.busy": "2024-06-24T17:24:35.820716Z", + "iopub.status.idle": "2024-06-24T17:24:49.878504Z", + "shell.execute_reply": "2024-06-24T17:24:49.876383Z" } }, "outputs": [], @@ -89,10 +89,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:51:38.083838Z", - "iopub.status.busy": "2024-06-23T21:51:38.082151Z", - "iopub.status.idle": "2024-06-23T21:51:38.091322Z", - "shell.execute_reply": "2024-06-23T21:51:38.089709Z" + "iopub.execute_input": "2024-06-24T17:24:49.887567Z", + "iopub.status.busy": "2024-06-24T17:24:49.885866Z", + "iopub.status.idle": "2024-06-24T17:24:49.894907Z", + "shell.execute_reply": "2024-06-24T17:24:49.893308Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:51:38.098209Z", - "iopub.status.busy": "2024-06-23T21:51:38.097164Z", - "iopub.status.idle": "2024-06-23T21:51:38.104930Z", - "shell.execute_reply": "2024-06-23T21:51:38.103319Z" + "iopub.execute_input": "2024-06-24T17:24:49.901784Z", + "iopub.status.busy": "2024-06-24T17:24:49.900780Z", + "iopub.status.idle": "2024-06-24T17:24:49.908561Z", + "shell.execute_reply": "2024-06-24T17:24:49.906966Z" } }, "outputs": [], @@ -147,10 +147,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:51:38.111998Z", - "iopub.status.busy": "2024-06-23T21:51:38.111406Z", - "iopub.status.idle": "2024-06-23T21:58:22.292924Z", - "shell.execute_reply": "2024-06-23T21:58:22.290866Z" + "iopub.execute_input": "2024-06-24T17:24:49.915758Z", + "iopub.status.busy": "2024-06-24T17:24:49.915189Z", + "iopub.status.idle": "2024-06-24T17:30:09.719766Z", + "shell.execute_reply": "2024-06-24T17:30:09.717758Z" } }, "outputs": [ @@ -158,21 +158,21 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 17:51:40,599 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" + "2024-06-24 13:24:52,532 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 17:51:59,829 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-06-24 13:25:13,433 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 17:51:59,831 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 16.893647 s\n" + "2024-06-24 13:25:13,434 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 18.668317 s\n" ] }, { @@ -196,14 +196,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 17:54:34,379 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-06-24 13:26:19,751 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 17:54:34,382 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 151.679064 s\n" + "2024-06-24 13:26:19,753 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 63.297405 s\n" ] }, { @@ -406,10 +406,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T21:58:22.301172Z", - "iopub.status.busy": "2024-06-23T21:58:22.300020Z", - "iopub.status.idle": "2024-06-23T21:58:22.685237Z", - "shell.execute_reply": "2024-06-23T21:58:22.683367Z" + "iopub.execute_input": "2024-06-24T17:30:09.728351Z", + "iopub.status.busy": "2024-06-24T17:30:09.726756Z", + "iopub.status.idle": "2024-06-24T17:30:10.521584Z", + "shell.execute_reply": "2024-06-24T17:30:10.519702Z" } }, "outputs": [ @@ -2407,9 +2407,9 @@ } }, "text/html": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# plotting the ROC curves for all the slices\n", - "roc_plot = plotter.roc_curve_comparison(roc_curves, aurocs=aurocs)\n", - "report.log_plotly_figure(\n", - " fig=roc_plot,\n", - " caption=\"ROC Curve Comparison\",\n", - " section_name=\"quantitative analysis\",\n", - ")\n", - "roc_plot.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": { - "execution": { - "iopub.execute_input": "2024-06-23T22:02:03.354278Z", - "iopub.status.busy": "2024-06-23T22:02:03.352611Z", - "iopub.status.idle": "2024-06-23T22:02:03.521278Z", - "shell.execute_reply": "2024-06-23T22:02:03.519512Z" - } - }, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "mode": "lines", - "name": "age:[20 - 50) (AUC = 0.20)", - "type": "scatter", - "x": [ - 1.0, - 1.0, - 1.0, - 1.0, - 1.0, - 1.0, - 1.0, - 1.0, - 1.0, 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Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:AveragePrecision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"6\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"11\": [\"metric:AveragePrecision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"12\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"16\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"17\": [\"metric:AveragePrecision\", \"gender:M\", \"age:overall_age\"], \"18\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"21\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"22\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"23\": [\"metric:AveragePrecision\", \"gender:F\", \"age:overall_age\"], \"24\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"25\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"26\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"27\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"28\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"], \"29\": [\"metric:AveragePrecision\", \"age:overall_age\", \"gender:overall_gender\"]}"); 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var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": true, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); + var passed_all = JSON.parse("{\"0\": false, \"1\": false, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": false, \"11\": false, \"12\": true, \"13\": false, \"14\": true, \"15\": false, \"16\": false, \"17\": false, \"18\": false, \"19\": false, \"20\": false, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": false, \"26\": true, \"27\": false, \"28\": true, \"29\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\", \"19\": \"Precision\", \"20\": \"Recall\", \"21\": \"F1 Score\", \"22\": \"AUROC\", \"23\": \"AveragePrecision\", \"24\": \"Accuracy\", \"25\": \"Precision\", \"26\": \"Recall\", \"27\": \"F1 Score\", \"28\": \"AUROC\", \"29\": \"AveragePrecision\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2669,7 +2669,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [24, 25, 26, 27, 28, 29] - var histories = JSON.parse("{\"0\": [\"0.9927007555961609\", \"0.9084577556659906\", \"0.9967123505250632\", \"0.9361637171500369\", \"0.7970945087177168\"], \"1\": [\"0.5\", \"0.5871161364713195\", \"0.6427614945669572\", \"0.7123207351031206\", \"0.7693962240641155\"], \"2\": [\"0.20000000298023224\", \"0.1250038868989642\", \"0.03259395329045932\", \"0.03319717901877138\", \"0.0\"], \"3\": [\"0.2857142984867096\", \"0.15099968687132234\", \"0.31955516966378655\", \"0.2078074856118015\", \"0.34403908703582164\"], \"4\": [\"0.8376470804214478\", \"0.851705052986469\", \"0.8549064019158588\", \"0.8715990099807263\", \"0.9083766863936913\"], \"5\": [\"0.20127536356449127\", \"0.22730227860628935\", \"0.22650506425281836\", \"0.1479281472634238\", \"0.3049563375425116\"], \"6\": [\"0.9754148721694946\", \"0.8693023091304493\", \"0.8829761838493525\", \"0.852504229229007\", \"0.8256869937362297\"], \"7\": [\"0.3478260934352875\", \"0.2719131707443655\", \"0.009444526819723409\", \"0.0\", \"0.0\"], \"8\": [\"0.24242424964904785\", \"0.3761319090848231\", \"0.43667014852713304\", \"0.4866882347011495\", \"0.4174179040861352\"], \"9\": [\"0.2857142984867096\", \"0.24497241222728497\", \"0.20308995383515835\", \"0.3301458050299214\", \"0.1531067913292969\"], \"10\": [\"0.8921904563903809\", \"0.8553745921639088\", \"0.7622205918111564\", \"0.8144962759724492\", \"0.9053699954080255\"], \"11\": [\"0.255609393119812\", \"0.20684319820018238\", \"0.2124718685109644\", \"0.17035875481360624\", \"0.19798325421505883\"], \"12\": [\"0.9728915691375732\", \"1.0\", \"1.0\", \"0.9795997167410667\", \"1.0\"], \"13\": [\"0.2800000011920929\", \"0.2582725874984817\", \"0.37238248588781087\", \"0.2435939528636595\", \"0.23137984171780207\"], \"14\": [\"0.2800000011920929\", \"0.37120425956456843\", \"0.29522356360055857\", \"0.21291825287340976\", \"0.3167588325082886\"], \"15\": [\"0.2800000011920929\", \"0.1854585053638812\", \"0.1739141294195912\", \"0.08457587414417689\", \"0.09803278069196336\"], \"16\": [\"0.8564236760139465\", \"0.9211616658239623\", \"0.8161455066742371\", \"0.7692510919701953\", \"0.9768927991487647\"], \"17\": [\"0.18138155341148376\", \"0.3836534063808792\", \"0.32758153272326956\", \"0.4113266996701133\", \"0.570285361295733\"], \"18\": [\"0.9790164232254028\", \"1.0\", \"1.0\", \"1.0\", \"0.964453883754515\"], \"19\": [\"0.3499999940395355\", \"0.3863954430145741\", \"0.24755652007061535\", \"0.5051159855045335\", \"0.49375728106831906\"], \"20\": [\"0.26923078298568726\", \"0.3038250697216256\", \"0.25850919457814997\", \"0.2518948811458642\", \"0.4459606481557118\"], \"21\": [\"0.30434781312942505\", \"0.23824684326423057\", \"0.20321435109957497\", \"0.2935219811348861\", \"0.31346873379591406\"], \"22\": [\"0.9008569717407227\", \"1.0\", \"1.0\", \"0.9140278427225832\", \"1.0\"], \"23\": [\"0.28123924136161804\", \"0.3762084986412605\", \"0.3306538281125844\", \"0.24729012034954972\", \"0.30802978646595547\"], \"24\": [\"0.9761654138565063\", \"1.0\", \"0.9389906906786338\", \"0.8338169486377209\", \"0.9372759027305281\"], \"25\": [\"0.31111112236976624\", \"0.3208377413980842\", \"0.3948946957047839\", \"0.31539736452749256\", \"0.3728005225544868\"], \"26\": [\"0.27450981736183167\", \"0.27961555028769025\", \"0.2999792434857541\", \"0.31526039999962985\", \"0.27444905495904626\"], \"27\": [\"0.2916666567325592\", \"0.25051975408216337\", \"0.31948167829640195\", \"0.29195289901624977\", \"0.19997201586106395\"], \"28\": [\"0.8802536129951477\", \"0.8857792893282364\", \"0.9536138581831235\", \"1.0\", \"0.9655741864371827\"], \"29\": [\"0.21615521609783173\", \"0.24735582070032103\", \"0.20091912397467232\", \"0.30567041309612497\", \"0.4337665892419137\"]}"); + var histories = JSON.parse("{\"0\": [\"0.9887005686759949\", \"0.967746888531569\", \"0.7988722971227535\", \"0.7227156808167013\", \"0.5789049147031029\"], \"1\": [\"0.1666666716337204\", \"0.2831065900181766\", \"0.2832962528492804\", \"0.22785194466750155\", \"0.1425106187308304\"], \"2\": [\"0.25\", \"0.17171564904247688\", \"0.2412675424417403\", \"0.2208135395363855\", \"0.3546386252164388\"], \"3\": [\"0.20000000298023224\", \"0.17060809029370924\", \"0.3458485469702073\", \"0.14431159478556393\", \"0.15497918742734113\"], \"4\": [\"0.9549005031585693\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"5\": [\"0.19111111760139465\", \"0.0767934276342555\", \"0.0\", \"0.1852804489314256\", \"0.15470952358482482\"], \"6\": [\"0.9605262875556946\", \"0.8530324490671806\", \"0.9300316341726008\", \"0.9310224510462368\", \"1.0\"], \"7\": [\"0.2586206793785095\", \"0.3469777657307169\", \"0.21437328975863362\", \"0.25301966752515564\", \"0.32745020900349925\"], \"8\": [\"0.4285714328289032\", \"0.4863162770756552\", \"0.3369498704728758\", \"0.3835171277524738\", \"0.4790486695571849\"], \"9\": [\"0.32258063554763794\", \"0.33066980215482006\", \"0.40967172859986245\", \"0.42904165260242966\", \"0.3994737200921887\"], \"10\": [\"0.8546901941299438\", \"0.7435493961123054\", \"0.6672667308661897\", \"0.6670253102304519\", \"0.687312438378646\"], \"11\": [\"0.2259426712989807\", \"0.08545486006585726\", \"0.112583513766943\", \"0.11853279888745971\", \"0.09345701709548149\"], \"12\": [\"0.9532846808433533\", \"0.9089871725865322\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.203125\", \"0.17437954813954526\", \"0.2033909885009927\", \"0.33660775890139927\", \"0.36452445556162427\"], \"14\": [\"0.5\", \"0.5599941291962557\", \"0.5399044579979728\", \"0.647208705934677\", \"0.7046981483734307\"], \"15\": [\"0.2888889014720917\", \"0.3591785064016164\", \"0.2587917301254642\", \"0.42647202845994686\", \"0.34559769331138124\"], \"16\": [\"0.8374541997909546\", \"0.8672055304196535\", \"0.7996155869097941\", \"0.6831016157398699\", \"0.6828152555302079\"], \"17\": [\"0.22076460719108582\", \"0.3074173340023777\", \"0.2889056015720513\", \"0.20629580359857563\", \"0.3292325684333645\"], \"18\": [\"0.9723533391952515\", \"0.8745150315596183\", \"0.7346915361806063\", \"0.6011739227711295\", \"0.614438884505949\"], \"19\": [\"0.28947368264198303\", \"0.28344567063124715\", \"0.27589206848200726\", \"0.05841015781923781\", \"0.20009379001937413\"], \"20\": [\"0.4399999976158142\", \"0.27594835271424334\", \"0.31405174359210797\", \"0.21502390592743492\", \"0.11449306433088469\"], \"21\": [\"0.3492063581943512\", \"0.36670964488891733\", \"0.32932537186911304\", \"0.44445337133168367\", \"0.48407854385912763\"], \"22\": [\"0.8986282348632812\", \"0.8724241882270548\", \"0.8130234252354724\", \"0.839015894056917\", \"0.6850477640088106\"], \"23\": [\"0.18307533860206604\", \"0.12451795962895128\", \"0.1314799185429758\", \"0.25838636704291396\", \"0.09907437189840479\"], \"24\": [\"0.9631966352462769\", \"0.9404148753084353\", \"1.0\", \"0.865537367237943\", \"0.9457656053798308\"], \"25\": [\"0.23529411852359772\", \"0.3353397698826702\", \"0.2347942587438357\", \"0.24940135358325163\", \"0.13723656640865858\"], \"26\": [\"0.47058823704719543\", \"0.5544302008785514\", \"0.6165886929090613\", \"0.638364515906015\", \"0.7718616837901301\"], \"27\": [\"0.3137255012989044\", \"0.2895395992281006\", \"0.23012424557828837\", \"0.2816935937763847\", \"0.44983329466792576\"], \"28\": [\"0.8678535223007202\", \"1.0\", \"1.0\", \"1.0\", \"0.8681896174958852\"], \"29\": [\"0.1931164562702179\", \"0.16590665345700772\", \"0.10659773352408844\", \"0.14689880818360085\", \"0.151096478209447\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2969,9 +2969,9 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:AveragePrecision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"6\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"11\": [\"metric:AveragePrecision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"12\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"16\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"17\": [\"metric:AveragePrecision\", \"gender:M\", \"age:overall_age\"], \"18\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"21\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"22\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"23\": [\"metric:AveragePrecision\", \"gender:F\", \"age:overall_age\"], \"24\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"25\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"26\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"27\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"28\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"], \"29\": [\"metric:AveragePrecision\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.9927007555961609\", \"0.9084577556659906\", \"0.9967123505250632\", \"0.9361637171500369\", \"0.7970945087177168\"], \"1\": [\"0.5\", \"0.5871161364713195\", \"0.6427614945669572\", \"0.7123207351031206\", \"0.7693962240641155\"], \"2\": [\"0.20000000298023224\", \"0.1250038868989642\", \"0.03259395329045932\", \"0.03319717901877138\", \"0.0\"], \"3\": [\"0.2857142984867096\", \"0.15099968687132234\", \"0.31955516966378655\", \"0.2078074856118015\", \"0.34403908703582164\"], \"4\": [\"0.8376470804214478\", \"0.851705052986469\", \"0.8549064019158588\", \"0.8715990099807263\", \"0.9083766863936913\"], \"5\": [\"0.20127536356449127\", \"0.22730227860628935\", \"0.22650506425281836\", \"0.1479281472634238\", \"0.3049563375425116\"], \"6\": [\"0.9754148721694946\", \"0.8693023091304493\", \"0.8829761838493525\", \"0.852504229229007\", \"0.8256869937362297\"], \"7\": [\"0.3478260934352875\", \"0.2719131707443655\", \"0.009444526819723409\", \"0.0\", \"0.0\"], \"8\": [\"0.24242424964904785\", \"0.3761319090848231\", \"0.43667014852713304\", \"0.4866882347011495\", \"0.4174179040861352\"], \"9\": [\"0.2857142984867096\", \"0.24497241222728497\", \"0.20308995383515835\", \"0.3301458050299214\", \"0.1531067913292969\"], \"10\": [\"0.8921904563903809\", \"0.8553745921639088\", \"0.7622205918111564\", \"0.8144962759724492\", \"0.9053699954080255\"], \"11\": [\"0.255609393119812\", \"0.20684319820018238\", \"0.2124718685109644\", \"0.17035875481360624\", \"0.19798325421505883\"], \"12\": [\"0.9728915691375732\", \"1.0\", \"1.0\", \"0.9795997167410667\", \"1.0\"], \"13\": [\"0.2800000011920929\", \"0.2582725874984817\", \"0.37238248588781087\", \"0.2435939528636595\", \"0.23137984171780207\"], \"14\": [\"0.2800000011920929\", \"0.37120425956456843\", \"0.29522356360055857\", \"0.21291825287340976\", \"0.3167588325082886\"], \"15\": [\"0.2800000011920929\", \"0.1854585053638812\", \"0.1739141294195912\", \"0.08457587414417689\", \"0.09803278069196336\"], \"16\": [\"0.8564236760139465\", \"0.9211616658239623\", \"0.8161455066742371\", \"0.7692510919701953\", \"0.9768927991487647\"], \"17\": [\"0.18138155341148376\", \"0.3836534063808792\", \"0.32758153272326956\", \"0.4113266996701133\", \"0.570285361295733\"], \"18\": [\"0.9790164232254028\", \"1.0\", \"1.0\", \"1.0\", \"0.964453883754515\"], \"19\": [\"0.3499999940395355\", \"0.3863954430145741\", \"0.24755652007061535\", \"0.5051159855045335\", \"0.49375728106831906\"], \"20\": [\"0.26923078298568726\", \"0.3038250697216256\", \"0.25850919457814997\", \"0.2518948811458642\", \"0.4459606481557118\"], \"21\": [\"0.30434781312942505\", \"0.23824684326423057\", \"0.20321435109957497\", \"0.2935219811348861\", \"0.31346873379591406\"], \"22\": [\"0.9008569717407227\", \"1.0\", \"1.0\", \"0.9140278427225832\", \"1.0\"], \"23\": [\"0.28123924136161804\", \"0.3762084986412605\", \"0.3306538281125844\", \"0.24729012034954972\", \"0.30802978646595547\"], \"24\": [\"0.9761654138565063\", \"1.0\", \"0.9389906906786338\", \"0.8338169486377209\", \"0.9372759027305281\"], \"25\": [\"0.31111112236976624\", \"0.3208377413980842\", \"0.3948946957047839\", \"0.31539736452749256\", \"0.3728005225544868\"], \"26\": [\"0.27450981736183167\", \"0.27961555028769025\", \"0.2999792434857541\", \"0.31526039999962985\", \"0.27444905495904626\"], \"27\": [\"0.2916666567325592\", \"0.25051975408216337\", \"0.31948167829640195\", \"0.29195289901624977\", \"0.19997201586106395\"], \"28\": [\"0.8802536129951477\", \"0.8857792893282364\", \"0.9536138581831235\", \"1.0\", \"0.9655741864371827\"], \"29\": [\"0.21615521609783173\", \"0.24735582070032103\", \"0.20091912397467232\", \"0.30567041309612497\", \"0.4337665892419137\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.9887005686759949\", \"0.967746888531569\", \"0.7988722971227535\", \"0.7227156808167013\", \"0.5789049147031029\"], \"1\": [\"0.1666666716337204\", \"0.2831065900181766\", \"0.2832962528492804\", \"0.22785194466750155\", \"0.1425106187308304\"], \"2\": [\"0.25\", \"0.17171564904247688\", \"0.2412675424417403\", \"0.2208135395363855\", \"0.3546386252164388\"], \"3\": [\"0.20000000298023224\", \"0.17060809029370924\", \"0.3458485469702073\", \"0.14431159478556393\", \"0.15497918742734113\"], \"4\": [\"0.9549005031585693\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"5\": [\"0.19111111760139465\", \"0.0767934276342555\", \"0.0\", \"0.1852804489314256\", \"0.15470952358482482\"], \"6\": [\"0.9605262875556946\", \"0.8530324490671806\", \"0.9300316341726008\", \"0.9310224510462368\", \"1.0\"], \"7\": [\"0.2586206793785095\", \"0.3469777657307169\", \"0.21437328975863362\", \"0.25301966752515564\", \"0.32745020900349925\"], \"8\": [\"0.4285714328289032\", \"0.4863162770756552\", \"0.3369498704728758\", \"0.3835171277524738\", \"0.4790486695571849\"], \"9\": [\"0.32258063554763794\", \"0.33066980215482006\", \"0.40967172859986245\", \"0.42904165260242966\", \"0.3994737200921887\"], \"10\": [\"0.8546901941299438\", \"0.7435493961123054\", \"0.6672667308661897\", \"0.6670253102304519\", \"0.687312438378646\"], \"11\": [\"0.2259426712989807\", \"0.08545486006585726\", \"0.112583513766943\", \"0.11853279888745971\", \"0.09345701709548149\"], \"12\": [\"0.9532846808433533\", \"0.9089871725865322\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.203125\", \"0.17437954813954526\", \"0.2033909885009927\", \"0.33660775890139927\", \"0.36452445556162427\"], \"14\": [\"0.5\", \"0.5599941291962557\", \"0.5399044579979728\", \"0.647208705934677\", \"0.7046981483734307\"], \"15\": [\"0.2888889014720917\", \"0.3591785064016164\", \"0.2587917301254642\", \"0.42647202845994686\", \"0.34559769331138124\"], \"16\": [\"0.8374541997909546\", \"0.8672055304196535\", \"0.7996155869097941\", \"0.6831016157398699\", \"0.6828152555302079\"], \"17\": [\"0.22076460719108582\", \"0.3074173340023777\", \"0.2889056015720513\", \"0.20629580359857563\", \"0.3292325684333645\"], \"18\": [\"0.9723533391952515\", \"0.8745150315596183\", \"0.7346915361806063\", \"0.6011739227711295\", \"0.614438884505949\"], \"19\": [\"0.28947368264198303\", \"0.28344567063124715\", \"0.27589206848200726\", \"0.05841015781923781\", \"0.20009379001937413\"], \"20\": [\"0.4399999976158142\", \"0.27594835271424334\", \"0.31405174359210797\", \"0.21502390592743492\", \"0.11449306433088469\"], \"21\": [\"0.3492063581943512\", \"0.36670964488891733\", \"0.32932537186911304\", \"0.44445337133168367\", \"0.48407854385912763\"], \"22\": [\"0.8986282348632812\", \"0.8724241882270548\", \"0.8130234252354724\", \"0.839015894056917\", \"0.6850477640088106\"], \"23\": [\"0.18307533860206604\", \"0.12451795962895128\", \"0.1314799185429758\", \"0.25838636704291396\", \"0.09907437189840479\"], \"24\": [\"0.9631966352462769\", \"0.9404148753084353\", \"1.0\", \"0.865537367237943\", \"0.9457656053798308\"], \"25\": [\"0.23529411852359772\", \"0.3353397698826702\", \"0.2347942587438357\", \"0.24940135358325163\", \"0.13723656640865858\"], \"26\": [\"0.47058823704719543\", \"0.5544302008785514\", \"0.6165886929090613\", \"0.638364515906015\", \"0.7718616837901301\"], \"27\": [\"0.3137255012989044\", \"0.2895395992281006\", \"0.23012424557828837\", \"0.2816935937763847\", \"0.44983329466792576\"], \"28\": [\"0.8678535223007202\", \"1.0\", \"1.0\", \"1.0\", \"0.8681896174958852\"], \"29\": [\"0.1931164562702179\", \"0.16590665345700772\", \"0.10659773352408844\", \"0.14689880818360085\", \"0.151096478209447\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": true, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); + var passed_all = JSON.parse("{\"0\": false, \"1\": false, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": false, \"11\": false, \"12\": true, \"13\": false, \"14\": true, \"15\": false, \"16\": false, \"17\": false, \"18\": false, \"19\": false, \"20\": false, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": false, \"26\": true, \"27\": false, \"28\": true, \"29\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\", \"19\": \"Precision\", \"20\": \"Recall\", \"21\": \"F1 Score\", \"22\": \"AUROC\", \"23\": \"AveragePrecision\", \"24\": \"Accuracy\", \"25\": \"Precision\", \"26\": \"Recall\", \"27\": \"F1 Score\", \"28\": \"AUROC\", \"29\": \"AveragePrecision\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -3484,7 +3484,7 @@

Ethical Considerations

]; // create global variable for max_n_evals - var histories = JSON.parse("{\"0\": [\"0.9927007555961609\", \"0.9084577556659906\", \"0.9967123505250632\", \"0.9361637171500369\", \"0.7970945087177168\"], \"1\": [\"0.5\", \"0.5871161364713195\", \"0.6427614945669572\", \"0.7123207351031206\", \"0.7693962240641155\"], \"2\": [\"0.20000000298023224\", \"0.1250038868989642\", \"0.03259395329045932\", \"0.03319717901877138\", \"0.0\"], \"3\": [\"0.2857142984867096\", \"0.15099968687132234\", \"0.31955516966378655\", \"0.2078074856118015\", \"0.34403908703582164\"], \"4\": [\"0.8376470804214478\", \"0.851705052986469\", \"0.8549064019158588\", \"0.8715990099807263\", \"0.9083766863936913\"], \"5\": [\"0.20127536356449127\", \"0.22730227860628935\", \"0.22650506425281836\", \"0.1479281472634238\", \"0.3049563375425116\"], \"6\": [\"0.9754148721694946\", \"0.8693023091304493\", \"0.8829761838493525\", \"0.852504229229007\", \"0.8256869937362297\"], \"7\": [\"0.3478260934352875\", \"0.2719131707443655\", \"0.009444526819723409\", \"0.0\", \"0.0\"], \"8\": [\"0.24242424964904785\", \"0.3761319090848231\", \"0.43667014852713304\", \"0.4866882347011495\", \"0.4174179040861352\"], \"9\": [\"0.2857142984867096\", \"0.24497241222728497\", \"0.20308995383515835\", \"0.3301458050299214\", \"0.1531067913292969\"], \"10\": [\"0.8921904563903809\", \"0.8553745921639088\", \"0.7622205918111564\", \"0.8144962759724492\", \"0.9053699954080255\"], \"11\": [\"0.255609393119812\", \"0.20684319820018238\", \"0.2124718685109644\", \"0.17035875481360624\", \"0.19798325421505883\"], \"12\": [\"0.9728915691375732\", \"1.0\", \"1.0\", \"0.9795997167410667\", \"1.0\"], \"13\": [\"0.2800000011920929\", \"0.2582725874984817\", \"0.37238248588781087\", \"0.2435939528636595\", \"0.23137984171780207\"], \"14\": [\"0.2800000011920929\", \"0.37120425956456843\", \"0.29522356360055857\", \"0.21291825287340976\", \"0.3167588325082886\"], \"15\": [\"0.2800000011920929\", \"0.1854585053638812\", \"0.1739141294195912\", \"0.08457587414417689\", \"0.09803278069196336\"], \"16\": [\"0.8564236760139465\", \"0.9211616658239623\", \"0.8161455066742371\", \"0.7692510919701953\", \"0.9768927991487647\"], \"17\": [\"0.18138155341148376\", \"0.3836534063808792\", \"0.32758153272326956\", \"0.4113266996701133\", \"0.570285361295733\"], \"18\": [\"0.9790164232254028\", \"1.0\", \"1.0\", \"1.0\", \"0.964453883754515\"], \"19\": [\"0.3499999940395355\", \"0.3863954430145741\", \"0.24755652007061535\", \"0.5051159855045335\", \"0.49375728106831906\"], \"20\": [\"0.26923078298568726\", \"0.3038250697216256\", \"0.25850919457814997\", \"0.2518948811458642\", \"0.4459606481557118\"], \"21\": [\"0.30434781312942505\", \"0.23824684326423057\", \"0.20321435109957497\", \"0.2935219811348861\", \"0.31346873379591406\"], \"22\": [\"0.9008569717407227\", \"1.0\", \"1.0\", \"0.9140278427225832\", \"1.0\"], \"23\": [\"0.28123924136161804\", \"0.3762084986412605\", \"0.3306538281125844\", \"0.24729012034954972\", \"0.30802978646595547\"], \"24\": [\"0.9761654138565063\", \"1.0\", \"0.9389906906786338\", \"0.8338169486377209\", \"0.9372759027305281\"], \"25\": [\"0.31111112236976624\", \"0.3208377413980842\", \"0.3948946957047839\", \"0.31539736452749256\", \"0.3728005225544868\"], \"26\": [\"0.27450981736183167\", \"0.27961555028769025\", \"0.2999792434857541\", \"0.31526039999962985\", \"0.27444905495904626\"], \"27\": [\"0.2916666567325592\", \"0.25051975408216337\", \"0.31948167829640195\", \"0.29195289901624977\", \"0.19997201586106395\"], \"28\": [\"0.8802536129951477\", \"0.8857792893282364\", \"0.9536138581831235\", \"1.0\", \"0.9655741864371827\"], \"29\": [\"0.21615521609783173\", \"0.24735582070032103\", \"0.20091912397467232\", \"0.30567041309612497\", \"0.4337665892419137\"]}"); + var histories = JSON.parse("{\"0\": [\"0.9887005686759949\", \"0.967746888531569\", \"0.7988722971227535\", \"0.7227156808167013\", \"0.5789049147031029\"], \"1\": [\"0.1666666716337204\", \"0.2831065900181766\", \"0.2832962528492804\", \"0.22785194466750155\", \"0.1425106187308304\"], \"2\": [\"0.25\", \"0.17171564904247688\", \"0.2412675424417403\", \"0.2208135395363855\", \"0.3546386252164388\"], \"3\": [\"0.20000000298023224\", \"0.17060809029370924\", \"0.3458485469702073\", \"0.14431159478556393\", \"0.15497918742734113\"], \"4\": [\"0.9549005031585693\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"5\": [\"0.19111111760139465\", \"0.0767934276342555\", \"0.0\", \"0.1852804489314256\", \"0.15470952358482482\"], \"6\": [\"0.9605262875556946\", \"0.8530324490671806\", \"0.9300316341726008\", \"0.9310224510462368\", \"1.0\"], \"7\": [\"0.2586206793785095\", \"0.3469777657307169\", \"0.21437328975863362\", \"0.25301966752515564\", \"0.32745020900349925\"], \"8\": [\"0.4285714328289032\", \"0.4863162770756552\", \"0.3369498704728758\", \"0.3835171277524738\", \"0.4790486695571849\"], \"9\": [\"0.32258063554763794\", \"0.33066980215482006\", \"0.40967172859986245\", \"0.42904165260242966\", \"0.3994737200921887\"], \"10\": [\"0.8546901941299438\", \"0.7435493961123054\", \"0.6672667308661897\", \"0.6670253102304519\", \"0.687312438378646\"], \"11\": [\"0.2259426712989807\", \"0.08545486006585726\", \"0.112583513766943\", \"0.11853279888745971\", \"0.09345701709548149\"], \"12\": [\"0.9532846808433533\", \"0.9089871725865322\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.203125\", \"0.17437954813954526\", \"0.2033909885009927\", \"0.33660775890139927\", \"0.36452445556162427\"], \"14\": [\"0.5\", \"0.5599941291962557\", \"0.5399044579979728\", \"0.647208705934677\", \"0.7046981483734307\"], \"15\": [\"0.2888889014720917\", \"0.3591785064016164\", \"0.2587917301254642\", \"0.42647202845994686\", \"0.34559769331138124\"], \"16\": [\"0.8374541997909546\", \"0.8672055304196535\", \"0.7996155869097941\", \"0.6831016157398699\", \"0.6828152555302079\"], \"17\": [\"0.22076460719108582\", \"0.3074173340023777\", \"0.2889056015720513\", \"0.20629580359857563\", \"0.3292325684333645\"], \"18\": [\"0.9723533391952515\", \"0.8745150315596183\", \"0.7346915361806063\", \"0.6011739227711295\", \"0.614438884505949\"], \"19\": [\"0.28947368264198303\", \"0.28344567063124715\", \"0.27589206848200726\", \"0.05841015781923781\", \"0.20009379001937413\"], \"20\": [\"0.4399999976158142\", \"0.27594835271424334\", \"0.31405174359210797\", \"0.21502390592743492\", \"0.11449306433088469\"], \"21\": [\"0.3492063581943512\", \"0.36670964488891733\", \"0.32932537186911304\", \"0.44445337133168367\", \"0.48407854385912763\"], \"22\": [\"0.8986282348632812\", \"0.8724241882270548\", \"0.8130234252354724\", \"0.839015894056917\", \"0.6850477640088106\"], \"23\": [\"0.18307533860206604\", \"0.12451795962895128\", \"0.1314799185429758\", \"0.25838636704291396\", \"0.09907437189840479\"], \"24\": [\"0.9631966352462769\", \"0.9404148753084353\", \"1.0\", \"0.865537367237943\", \"0.9457656053798308\"], \"25\": [\"0.23529411852359772\", \"0.3353397698826702\", \"0.2347942587438357\", \"0.24940135358325163\", \"0.13723656640865858\"], \"26\": [\"0.47058823704719543\", \"0.5544302008785514\", \"0.6165886929090613\", \"0.638364515906015\", \"0.7718616837901301\"], \"27\": [\"0.3137255012989044\", \"0.2895395992281006\", \"0.23012424557828837\", \"0.2816935937763847\", \"0.44983329466792576\"], \"28\": [\"0.8678535223007202\", \"1.0\", \"1.0\", \"1.0\", \"0.8681896174958852\"], \"29\": [\"0.1931164562702179\", \"0.16590665345700772\", \"0.10659773352408844\", \"0.14689880818360085\", \"0.151096478209447\"]}"); // get max_n_evals from histories var history_data = []; for (let i = 0; i < histories[0].length; i++) { diff --git a/api/tutorials/nihcxr/cxr_classification.html b/api/tutorials/nihcxr/cxr_classification.html index 21a813919..e6008efe8 100644 --- a/api/tutorials/nihcxr/cxr_classification.html +++ b/api/tutorials/nihcxr/cxr_classification.html @@ -459,13 +459,13 @@

Model Creation

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Multilabel AUROC by Pathology and Sex

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@@ -609,61 +609,61 @@

Multilabel AUROC by Pathology and Age
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[8]:
@@ -717,9 +717,9 @@ 
Multilabel AUROC by Pathology and Age
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diff --git a/api/tutorials/nihcxr/cxr_classification.ipynb b/api/tutorials/nihcxr/cxr_classification.ipynb index 08fd3a94d..054c898a0 100644 --- a/api/tutorials/nihcxr/cxr_classification.ipynb +++ b/api/tutorials/nihcxr/cxr_classification.ipynb @@ -24,10 +24,10 @@ "id": "fc1eb72a", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:02:21.218105Z", - "iopub.status.busy": "2024-06-23T22:02:21.217108Z", - "iopub.status.idle": "2024-06-23T22:02:38.876547Z", - "shell.execute_reply": "2024-06-23T22:02:38.874123Z" + "iopub.execute_input": "2024-06-24T17:44:11.439383Z", + "iopub.status.busy": "2024-06-24T17:44:11.438051Z", + "iopub.status.idle": "2024-06-24T17:44:43.859430Z", + "shell.execute_reply": "2024-06-24T17:44:43.856977Z" } }, "outputs": [], @@ -69,10 +69,10 @@ "id": "25c2a16f", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:02:38.887710Z", - "iopub.status.busy": "2024-06-23T22:02:38.884978Z", - "iopub.status.idle": "2024-06-23T22:26:14.057193Z", - "shell.execute_reply": "2024-06-23T22:26:14.054621Z" + "iopub.execute_input": "2024-06-24T17:44:43.867594Z", + "iopub.status.busy": "2024-06-24T17:44:43.866148Z", + "iopub.status.idle": "2024-06-24T18:07:46.671101Z", + "shell.execute_reply": "2024-06-24T18:07:46.668088Z" }, "nbsphinx": "hidden" }, @@ -90,32 +90,11 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|########| 1000/1000 [04:22<00:00, 3.81 examples/s]" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", - "Flattening the indices: 100%|########| 1000/1000 [04:22<00:00, 3.80 examples/s]\r\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Flattening the indices: 100%|########| 1000/1000 [04:19<00:00, 3.85 examples/s]\r", + "Flattening the indices: 100%|########| 1000/1000 [04:19<00:00, 3.85 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/400 [00:00 Patient Gender:M: 100%|###| 400/400 [00:00<00:00, 36546.10 examples/s]\r\n" + "Filter -> Patient Gender:M: 100%|###| 400/400 [00:00<00:00, 37716.87 examples/s]\r\n" ] }, { @@ -166,7 +146,8 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Gender:F: 0%| | 0/400 [00:00 Patient Gender:F: 0%| | 0/400 [00:00 Patient Gender:F: 100%|###| 400/400 [00:00<00:00, 38789.46 examples/s]\r\n" ] }, { @@ -174,7 +155,8 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Gender:F: 100%|###| 400/400 [00:00<00:00, 37044.79 examples/s]\r\n" + "Filter -> overall: 0%| | 0/400 [00:00 overall: 100%|############| 400/400 [00:00<00:00, 42370.99 examples/s]\r\n" ] }, { @@ -182,8 +164,8 @@ "output_type": "stream", "text": [ "\r", - "Filter -> overall: 0%| | 0/400 [00:00 overall: 100%|############| 400/400 [00:00<00:00, 40691.77 examples/s]\r\n" + "Filter -> Patient Age:[19 - 35]: 0%| | 0/400 [00:00 Patient Age:[19 - 35]: 100%|#| 400/400 [00:00<00:00, 33254.48 examples\r\n" ] }, { @@ -191,10 +173,8 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Age:[19 - 35]: 0%| | 0/400 [00:00 Patient Age:[19 - 35]: 100%|#| 400/400 [00:00<00:00, 31785.87 examples\r\n", - "\r", - "Filter -> Patient Age:[35 - 65]: 0%| | 0/400 [00:00 Patient Age:[35 - 65]: 0%| | 0/400 [00:00 Patient Age:[35 - 65]: 100%|#| 400/400 [00:00<00:00, 33720.34 examples\r\n" ] }, { @@ -202,7 +182,7 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Age:[35 - 65]: 100%|#| 400/400 [00:00<00:00, 33797.78 examples\r\n" + "Filter -> Patient Age:[65 - 100]: 0%| | 0/400 [00:00 Patient Age:[65 - 100]: 0%| | 0/400 [00:00 Patient Age:[65 - 100]: 100%|#| 400/400 [00:00<00:00, 33662.83 example\r\n" + "Filter -> Patient Age:[65 - 100]: 100%|#| 400/400 [00:00<00:00, 33532.30 example\r\n", + "\r", + "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/400 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/400 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|#| 400/400 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/400 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/400 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 100%|#| 400/400 [00:00<00:00, \r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|#| 400/400 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/400 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|#| 400/400 [00:00<00:00, \r\n" @@ -251,25 +230,20 @@ "text": [ "\r", "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 0%| | 0/400 [00:00 Patient Age:[65 - 100]&Patient Gender:M: 100%|#| 400/400 [00:00<00:00,\r\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|#| 400/400 [00:00<00:00,\r\n", "\r", - "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/400 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|#| 400/400 [00:00<00:00,\r\n" + "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/400 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|#| 400/400 [00:00<00:00,\r\n", "\r", "Filter -> overall: 0%| | 0/400 [00:00 overall: 100%|############| 400/400 [00:00<00:00, 40874.18 examples/s]\r\n" + "Filter -> overall: 100%|############| 400/400 [00:00<00:00, 41135.75 examples/s]\r\n" ] }, { @@ -285,27 +259,21 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|########| 1000/1000 [03:47<00:00, 4.40 examples/s]" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", - "Flattening the indices: 100%|########| 1000/1000 [03:47<00:00, 4.40 examples/s]\r\n", + "Flattening the indices: 100%|########| 1000/1000 [04:13<00:00, 3.94 examples/s]\r", + "Flattening the indices: 100%|########| 1000/1000 [04:13<00:00, 3.94 examples/s]\r\n", "\r", - "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/396 [00:00 Patient Gender:M: 100%|###| 396/396 [00:00<00:00, 37665.70 examples/s]\r\n" + "Filter -> Patient Gender:M: 100%|###| 396/396 [00:00<00:00, 37289.40 examples/s]\r\n" ] }, { @@ -350,7 +318,7 @@ "text": [ "\r", "Filter -> Patient Gender:F: 0%| | 0/396 [00:00 Patient Gender:F: 100%|###| 396/396 [00:00<00:00, 39299.27 examples/s]\r\n" + "Filter -> Patient Gender:F: 100%|###| 396/396 [00:00<00:00, 39258.40 examples/s]\r\n" ] }, { @@ -359,7 +327,7 @@ "text": [ "\r", "Filter -> overall: 0%| | 0/396 [00:00 overall: 100%|############| 396/396 [00:00<00:00, 42559.94 examples/s]\r\n" + "Filter -> overall: 100%|############| 396/396 [00:00<00:00, 42034.33 examples/s]\r\n" ] }, { @@ -368,7 +336,7 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/396 [00:00 Patient Age:[19 - 35]: 100%|#| 396/396 [00:00<00:00, 33314.83 examples\r\n" + "Filter -> Patient Age:[19 - 35]: 100%|#| 396/396 [00:00<00:00, 33261.46 examples\r\n" ] }, { @@ -377,7 +345,7 @@ "text": [ "\r", "Filter -> Patient Age:[35 - 65]: 0%| | 0/396 [00:00 Patient Age:[35 - 65]: 100%|#| 396/396 [00:00<00:00, 34426.57 examples\r\n" + "Filter -> Patient Age:[35 - 65]: 100%|#| 396/396 [00:00<00:00, 34256.16 examples\r\n" ] }, { @@ -386,7 +354,7 @@ "text": [ "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/396 [00:00 Patient Age:[65 - 100]: 100%|#| 396/396 [00:00<00:00, 35032.15 example\r\n" + "Filter -> Patient Age:[65 - 100]: 100%|#| 396/396 [00:00<00:00, 34417.30 example\r\n" ] }, { @@ -445,7 +413,7 @@ "output_type": "stream", "text": [ "\r", - "Filter -> overall: 100%|############| 396/396 [00:00<00:00, 42623.29 examples/s]\r\n" + "Filter -> overall: 100%|############| 396/396 [00:00<00:00, 42478.31 examples/s]\r\n" ] }, { @@ -461,8 +429,7 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|########| 1000/1000 [03:48<00:00, 4.38 examples/s]\r", - "Flattening the indices: 100%|########| 1000/1000 [03:48<00:00, 4.38 examples/s]\r\n" + "Flattening the indices: 100%|########| 1000/1000 [04:18<00:00, 3.87 examples/s]" ] }, { @@ -470,17 +437,19 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/383 [00:00 Patient Gender:M: 100%|###| 383/383 [00:00<00:00, 35679.95 examples/s]\r\n" + "Filter -> Patient Gender:M: 0%| | 0/383 [00:00 Patient Gender:M: 100%|###| 383/383 [00:00<00:00, 36101.72 examples/s]\r\n" ] }, { @@ -525,7 +493,7 @@ "text": [ "\r", "Filter -> Patient Gender:F: 0%| | 0/383 [00:00 Patient Gender:F: 100%|###| 383/383 [00:00<00:00, 37679.28 examples/s]\r\n" + "Filter -> Patient Gender:F: 100%|###| 383/383 [00:00<00:00, 37490.22 examples/s]\r\n" ] }, { @@ -534,7 +502,7 @@ "text": [ "\r", "Filter -> overall: 0%| | 0/383 [00:00 overall: 100%|############| 383/383 [00:00<00:00, 40034.35 examples/s]\r\n" + "Filter -> overall: 100%|############| 383/383 [00:00<00:00, 40124.35 examples/s]\r\n" ] }, { @@ -543,9 +511,7 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/383 [00:00 Patient Age:[19 - 35]: 100%|#| 383/383 [00:00<00:00, 31897.43 examples\r\n", - "\r", - "Filter -> Patient Age:[35 - 65]: 0%| | 0/383 [00:00 Patient Age:[19 - 35]: 100%|#| 383/383 [00:00<00:00, 32054.00 examples\r\n" ] }, { @@ -553,7 +519,8 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Age:[35 - 65]: 100%|#| 383/383 [00:00<00:00, 33505.44 examples\r\n" + "Filter -> Patient Age:[35 - 65]: 0%| | 0/383 [00:00 Patient Age:[35 - 65]: 100%|#| 383/383 [00:00<00:00, 33513.13 examples\r\n" ] }, { @@ -562,7 +529,7 @@ "text": [ "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/383 [00:00 Patient Age:[65 - 100]: 100%|#| 383/383 [00:00<00:00, 33638.75 example\r\n" + "Filter -> Patient Age:[65 - 100]: 100%|#| 383/383 [00:00<00:00, 33715.70 example\r\n" ] }, { @@ -571,9 +538,7 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/383 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|#| 383/383 [00:00<00:00, \r\n", - "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|#| 383/383 [00:00<00:00, \r\n" ] }, { @@ -581,6 +546,7 @@ "output_type": "stream", "text": [ "\r", + "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 100%|#| 383/383 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/383 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|#| 383/383 [00:00<00:00,\r\n", "\r", - "Filter -> overall: 0%| | 0/383 [00:00 overall: 100%|############| 383/383 [00:00<00:00, 41053.37 examples/s]\r\n" + "Filter -> overall: 0%| | 0/383 [00:00 overall: 100%|############| 383/383 [00:00<00:00, 41051.27 examples/s]\r\n" ] }, { @@ -630,7 +603,7 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|########| 1000/1000 [03:47<00:00, 4.40 examples/s]" + "Flattening the indices: 100%|########| 1000/1000 [04:34<00:00, 3.64 examples/s]" ] }, { @@ -638,10 +611,10 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|########| 1000/1000 [03:47<00:00, 4.40 examples/s]\r\n", + "Flattening the indices: 100%|########| 1000/1000 [04:34<00:00, 3.64 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/411 [00:00 Patient Gender:M: 100%|###| 411/411 [00:00<00:00, 37922.85 examples/s]\r\n" + "Filter -> Patient Gender:M: 100%|###| 411/411 [00:00<00:00, 38129.19 examples/s]\r\n" ] }, { @@ -694,7 +667,8 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Gender:F: 0%| | 0/411 [00:00 Patient Gender:F: 0%| | 0/411 [00:00 Patient Gender:F: 100%|###| 411/411 [00:00<00:00, 39094.20 examples/s]\r\n" ] }, { @@ -702,7 +676,8 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Gender:F: 100%|###| 411/411 [00:00<00:00, 38649.81 examples/s]\r\n" + "Filter -> overall: 0%| | 0/411 [00:00 overall: 100%|############| 411/411 [00:00<00:00, 42486.79 examples/s]\r\n" ] }, { @@ -710,8 +685,7 @@ "output_type": "stream", "text": [ "\r", - "Filter -> overall: 0%| | 0/411 [00:00 overall: 100%|############| 411/411 [00:00<00:00, 42724.77 examples/s]\r\n" + "Filter -> Patient Age:[19 - 35]: 0%| | 0/411 [00:00 Patient Age:[19 - 35]: 0%| | 0/411 [00:00 Patient Age:[19 - 35]: 100%|#| 411/411 [00:00<00:00, 33878.88 examples\r\n", + "Filter -> Patient Age:[19 - 35]: 100%|#| 411/411 [00:00<00:00, 32944.60 examples\r\n", "\r", "Filter -> Patient Age:[35 - 65]: 0%| | 0/411 [00:00 Patient Age:[35 - 65]: 100%|#| 411/411 [00:00<00:00, 34522.06 examples\r\n" + "Filter -> Patient Age:[35 - 65]: 100%|#| 411/411 [00:00<00:00, 34186.59 examples\r\n" ] }, { @@ -739,7 +712,9 @@ "text": [ "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/411 [00:00 Patient Age:[65 - 100]: 100%|#| 411/411 [00:00<00:00, 34867.70 example\r\n" + "Filter -> Patient Age:[65 - 100]: 100%|#| 411/411 [00:00<00:00, 34626.77 example\r\n", + "\r", + "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|#| 411/411 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/411 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/411 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 100%|#| 411/411 [00:00<00:00, \r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|#| 411/411 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|#| 411/411 [00:00<00:00, \r\n" @@ -798,7 +771,7 @@ "output_type": "stream", "text": [ "\r", - "Filter -> overall: 100%|############| 411/411 [00:00<00:00, 43477.99 examples/s]\r\n" + "Filter -> overall: 100%|############| 411/411 [00:00<00:00, 43307.60 examples/s]\r\n" ] } ], @@ -846,10 +819,10 @@ "id": "03edf1c0", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:26:14.068519Z", - "iopub.status.busy": "2024-06-23T22:26:14.066936Z", - "iopub.status.idle": "2024-06-23T22:26:14.077573Z", - "shell.execute_reply": "2024-06-23T22:26:14.075919Z" + "iopub.execute_input": "2024-06-24T18:07:46.682007Z", + "iopub.status.busy": "2024-06-24T18:07:46.681090Z", + "iopub.status.idle": "2024-06-24T18:07:46.692326Z", + "shell.execute_reply": "2024-06-24T18:07:46.690552Z" } }, "outputs": [], @@ -871,10 +844,10 @@ "id": "6514120e", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:26:14.084775Z", - "iopub.status.busy": "2024-06-23T22:26:14.083777Z", - "iopub.status.idle": "2024-06-23T22:26:32.647182Z", - "shell.execute_reply": "2024-06-23T22:26:32.645498Z" + "iopub.execute_input": "2024-06-24T18:07:46.699706Z", + "iopub.status.busy": "2024-06-24T18:07:46.698617Z", + "iopub.status.idle": "2024-06-24T18:08:05.356955Z", + "shell.execute_reply": "2024-06-24T18:08:05.355293Z" } }, "outputs": [], @@ -918,17 +891,17 @@ "id": "5f624ed4", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:26:32.655225Z", - "iopub.status.busy": "2024-06-23T22:26:32.653890Z", - "iopub.status.idle": "2024-06-23T22:27:10.912265Z", - "shell.execute_reply": "2024-06-23T22:27:10.910336Z" + "iopub.execute_input": "2024-06-24T18:08:05.365740Z", + "iopub.status.busy": "2024-06-24T18:08:05.364198Z", + "iopub.status.idle": "2024-06-24T18:08:31.882897Z", + "shell.execute_reply": "2024-06-24T18:08:31.880743Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ed25d3e69d484e84ab7faa046dc5801c", + "model_id": "f9654f5126d3471988642923a0af8e97", "version_major": 2, "version_minor": 0 }, @@ -942,7 +915,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5d3d684bc32a4a30b0fa0f96f2bc6b89", + "model_id": "9d812e1f25b14aeb9bcc146204c54ca8", "version_major": 2, "version_minor": 0 }, @@ -1002,17 +975,17 @@ "id": "bff27cc1", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:27:10.921443Z", - "iopub.status.busy": "2024-06-23T22:27:10.920292Z", - "iopub.status.idle": "2024-06-23T22:27:11.335425Z", - "shell.execute_reply": "2024-06-23T22:27:11.333673Z" + "iopub.execute_input": "2024-06-24T18:08:31.892408Z", + "iopub.status.busy": "2024-06-24T18:08:31.890870Z", + "iopub.status.idle": "2024-06-24T18:08:32.310861Z", + "shell.execute_reply": "2024-06-24T18:08:32.309076Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "03057c0ca81948f8b77c0d22b215bebe", + "model_id": "eec83a9372ec4785a2b6c307b5170c52", "version_major": 2, "version_minor": 0 }, @@ -1026,7 +999,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8be08c3570444b65afcb8719ec5b0300", + "model_id": "f12505ef6ae441f4acc08a798fa4c720", "version_major": 2, "version_minor": 0 }, @@ -1040,7 +1013,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "098b4fa7c4044e1d8a6b3515687c28df", + "model_id": "21bf9139d61d4975b43620e025076bff", "version_major": 2, "version_minor": 0 }, @@ -1118,17 +1091,17 @@ "id": "8c38ef9e", "metadata": { "execution": { - 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Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8636363744735718\", \"0.92886081112948\", \"1.0\", \"0.8388038334314838\", \"0.8271875657967567\"], \"1\": [\"0.9795918464660645\", \"1.0\", \"0.982543943359856\", \"1.0\", \"1.0\"], \"2\": [\"0.774193525314331\", \"0.8243560838953359\", \"0.995089381881134\", \"1.0\", \"0.9412026289459778\"], \"3\": [\"0.8648648858070374\", \"0.8162655767088807\", \"0.7795336085778017\", \"0.7411887914229585\", \"0.8083397554971863\"], \"4\": [\"0.9410282373428345\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"5\": [\"0.8947368264198303\", \"1.0\", \"1.0\", \"0.9417175273644387\", \"1.0\"], \"6\": [\"0.875\", \"0.8395464300133455\", \"0.7456776102241438\", \"0.7379193629190488\", \"0.7301023910352686\"], \"7\": [\"0.9333333373069763\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"8\": [\"0.9032257795333862\", \"0.8832691274412479\", \"0.898138741685616\", \"0.8053984822297517\", \"0.7001154768020333\"], \"9\": [\"0.9358024001121521\", \"0.723815473128497\", \"0.7624543787388742\", \"0.822502223319343\", \"0.8275619527545803\"], \"10\": [\"0.8861788511276245\", \"0.9405222040176702\", \"0.9577679141433092\", \"0.8603178410811596\", \"0.9197755518663465\"], \"11\": [\"0.9750000238418579\", \"0.8782885107832065\", \"0.8367072960272697\", \"0.7986760129835162\", \"0.9105716497643859\"], \"12\": [\"0.8666666746139526\", \"0.9251160091099873\", \"0.746263327514448\", \"0.8748620924287724\", \"1.0\"], \"13\": [\"0.9176470637321472\", \"0.8991453249174426\", \"1.0\", \"0.9811549933268298\", \"0.9570742194944619\"], \"14\": [\"0.9537037014961243\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"15\": [\"0.9126213788986206\", \"0.95590361651259\", \"0.8577341451663933\", \"0.799358726729822\", \"0.809309780504532\"], \"16\": [\"0.942307710647583\", \"0.9506323824318652\", \"1.0\", \"1.0\", \"1.0\"], \"17\": [\"0.8909090757369995\", \"0.9458597618150345\", \"1.0\", \"1.0\", \"0.9593212131992811\"], \"18\": [\"0.9158878326416016\", \"0.8326578128511968\", \"0.8022102546108545\", \"1.0\", \"0.8879098256031821\"], \"19\": [\"0.9621212482452393\", \"1.0\", \"0.9688050743369877\", \"0.9954941235609506\", \"0.9783148891769534\"], \"20\": [\"0.8982300758361816\", \"0.857543273758781\", \"0.904582479269161\", \"0.9808626574410144\", \"0.8590755384678712\"], \"21\": [\"0.9621211886405945\", \"1.0\", \"1.0\", \"1.0\", \"0.9915753120646987\"], \"22\": [\"0.8758620619773865\", \"1.0\", \"1.0\", \"1.0\", \"0.9595588659073383\"], \"23\": [\"0.916967511177063\", \"0.9251057231160493\", \"0.9417636941765279\", \"1.0\", \"0.8515125521376568\"], \"24\": [\"0.9577693343162537\", \"0.9319297591011309\", \"0.9925472053943316\", \"1.0\", \"0.7621692516448988\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8442623019218445\", \"0.8228368850054627\", \"0.7625017470167952\", \"0.5872114690564066\", \"0.6471566536176281\"], \"1\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"0.9238540508253836\"], \"2\": [\"0.7164179086685181\", \"0.5260483546090627\", \"0.6667243013678141\", \"0.6583806400144895\", \"0.7824903970800032\"], \"3\": [\"0.834782600402832\", \"0.7699832445094515\", \"0.7621212758948609\", \"0.7514016602112257\", \"0.829238844116853\"], \"4\": [\"0.9251017570495605\", \"0.9603802175025565\", \"1.0\", \"1.0\", \"0.9921543953777135\"], \"5\": [\"0.8936170339584351\", \"0.8546169099506077\", \"0.8087788323321982\", \"0.7608500038433639\", \"0.9670667620962246\"], \"6\": [\"0.9583333134651184\", \"0.8308840458434986\", \"0.8016947775667752\", \"0.724680539413762\", \"0.8372601591293443\"], \"7\": [\"0.8518518805503845\", \"0.8134346033673987\", \"0.6379958916526355\", \"0.6576201852361977\", \"0.6569282213102983\"], \"8\": [\"0.9019607901573181\", \"1.0\", \"1.0\", \"1.0\", \"0.8802982536952462\"], \"9\": [\"0.9777777791023254\", \"0.808717328320772\", \"0.8389433885147825\", \"0.6803208424373841\", \"0.515650933392587\"], \"10\": [\"0.8863636255264282\", \"0.7183964953663242\", \"0.8539788722377375\", \"0.8239444528752622\", \"0.7916176207368374\"], \"11\": [\"0.9756097793579102\", \"0.9151657232716784\", \"0.8866428394307877\", \"0.8021404089798435\", \"0.7698366511555069\"], \"12\": [\"0.8602150678634644\", \"0.8208044784812699\", \"0.9643979742488535\", \"1.0\", \"1.0\"], \"13\": [\"0.9142857193946838\", \"1.0\", \"0.9987962920826111\", \"0.9931703249329342\", \"0.9298918574620448\"], \"14\": [\"0.9572649598121643\", \"0.9777604219825083\", \"0.8032522673188167\", \"0.7961315146673383\", \"0.9042605905028186\"], \"15\": [\"0.8723404407501221\", \"0.8709851494586376\", \"0.6967891162596921\", \"0.6517295812764629\", \"0.6125280701743805\"], \"16\": [\"0.976190447807312\", \"1.0\", \"1.0\", \"1.0\", \"0.9059552696508648\"], \"17\": [\"0.7884615659713745\", \"0.7043630550644677\", \"0.7229077021863914\", \"0.5927093692988337\", \"0.7270607767583099\"], \"18\": [\"0.8723404407501221\", \"0.862068838895013\", \"0.8269709765142678\", \"0.8656156891888379\", \"0.9681075499404925\"], \"19\": [\"0.9434523582458496\", \"0.8899209417460925\", \"0.8487447479024821\", \"1.0\", \"0.8721629592302116\"], \"20\": [\"0.8805309534072876\", \"0.8320116365014649\", \"0.882529253790269\", \"0.8538288072289105\", \"0.6972831117927905\"], \"21\": [\"0.975806474685669\", \"1.0\", \"0.9563597638857201\", \"1.0\", \"0.96807231313915\"], \"22\": [\"0.834482729434967\", \"0.8166716034156569\", \"0.9404187943552825\", \"1.0\", \"1.0\"], \"23\": [\"0.8996282815933228\", \"0.7029612217706456\", \"0.7692661089614848\", \"0.8477150138236433\", \"0.8026081133799058\"], \"24\": [\"0.9500638246536255\", \"1.0\", \"1.0\", \"0.9786707018398783\", \"1.0\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); + var passed_all = JSON.parse("{\"0\": false, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": false, \"8\": true, \"9\": false, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": false, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": false, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2571,7 +2571,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [20, 21, 22, 23, 24] - var histories = JSON.parse("{\"0\": [\"0.8636363744735718\", \"0.92886081112948\", \"1.0\", \"0.8388038334314838\", \"0.8271875657967567\"], \"1\": [\"0.9795918464660645\", \"1.0\", \"0.982543943359856\", \"1.0\", \"1.0\"], \"2\": [\"0.774193525314331\", \"0.8243560838953359\", \"0.995089381881134\", \"1.0\", \"0.9412026289459778\"], \"3\": [\"0.8648648858070374\", \"0.8162655767088807\", \"0.7795336085778017\", \"0.7411887914229585\", \"0.8083397554971863\"], \"4\": [\"0.9410282373428345\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"5\": [\"0.8947368264198303\", \"1.0\", \"1.0\", \"0.9417175273644387\", \"1.0\"], \"6\": [\"0.875\", \"0.8395464300133455\", \"0.7456776102241438\", \"0.7379193629190488\", \"0.7301023910352686\"], \"7\": [\"0.9333333373069763\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"8\": [\"0.9032257795333862\", \"0.8832691274412479\", \"0.898138741685616\", \"0.8053984822297517\", \"0.7001154768020333\"], \"9\": [\"0.9358024001121521\", \"0.723815473128497\", \"0.7624543787388742\", \"0.822502223319343\", \"0.8275619527545803\"], \"10\": [\"0.8861788511276245\", \"0.9405222040176702\", \"0.9577679141433092\", \"0.8603178410811596\", \"0.9197755518663465\"], \"11\": [\"0.9750000238418579\", \"0.8782885107832065\", \"0.8367072960272697\", \"0.7986760129835162\", \"0.9105716497643859\"], \"12\": [\"0.8666666746139526\", \"0.9251160091099873\", \"0.746263327514448\", \"0.8748620924287724\", \"1.0\"], \"13\": [\"0.9176470637321472\", \"0.8991453249174426\", \"1.0\", \"0.9811549933268298\", \"0.9570742194944619\"], \"14\": [\"0.9537037014961243\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"15\": [\"0.9126213788986206\", \"0.95590361651259\", \"0.8577341451663933\", \"0.799358726729822\", \"0.809309780504532\"], \"16\": [\"0.942307710647583\", \"0.9506323824318652\", \"1.0\", \"1.0\", \"1.0\"], \"17\": [\"0.8909090757369995\", \"0.9458597618150345\", \"1.0\", \"1.0\", \"0.9593212131992811\"], \"18\": [\"0.9158878326416016\", \"0.8326578128511968\", \"0.8022102546108545\", \"1.0\", \"0.8879098256031821\"], \"19\": [\"0.9621212482452393\", \"1.0\", \"0.9688050743369877\", \"0.9954941235609506\", \"0.9783148891769534\"], \"20\": [\"0.8982300758361816\", \"0.857543273758781\", \"0.904582479269161\", \"0.9808626574410144\", \"0.8590755384678712\"], \"21\": [\"0.9621211886405945\", \"1.0\", \"1.0\", \"1.0\", \"0.9915753120646987\"], \"22\": [\"0.8758620619773865\", \"1.0\", \"1.0\", \"1.0\", \"0.9595588659073383\"], \"23\": [\"0.916967511177063\", \"0.9251057231160493\", \"0.9417636941765279\", \"1.0\", \"0.8515125521376568\"], \"24\": [\"0.9577693343162537\", \"0.9319297591011309\", \"0.9925472053943316\", \"1.0\", \"0.7621692516448988\"]}"); + var histories = JSON.parse("{\"0\": [\"0.8442623019218445\", \"0.8228368850054627\", \"0.7625017470167952\", \"0.5872114690564066\", \"0.6471566536176281\"], \"1\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"0.9238540508253836\"], \"2\": [\"0.7164179086685181\", \"0.5260483546090627\", \"0.6667243013678141\", \"0.6583806400144895\", \"0.7824903970800032\"], \"3\": [\"0.834782600402832\", \"0.7699832445094515\", \"0.7621212758948609\", \"0.7514016602112257\", \"0.829238844116853\"], \"4\": [\"0.9251017570495605\", \"0.9603802175025565\", \"1.0\", \"1.0\", \"0.9921543953777135\"], \"5\": [\"0.8936170339584351\", \"0.8546169099506077\", \"0.8087788323321982\", \"0.7608500038433639\", \"0.9670667620962246\"], \"6\": [\"0.9583333134651184\", \"0.8308840458434986\", \"0.8016947775667752\", \"0.724680539413762\", \"0.8372601591293443\"], \"7\": [\"0.8518518805503845\", \"0.8134346033673987\", \"0.6379958916526355\", \"0.6576201852361977\", \"0.6569282213102983\"], \"8\": [\"0.9019607901573181\", \"1.0\", \"1.0\", \"1.0\", \"0.8802982536952462\"], \"9\": [\"0.9777777791023254\", \"0.808717328320772\", \"0.8389433885147825\", \"0.6803208424373841\", \"0.515650933392587\"], \"10\": [\"0.8863636255264282\", \"0.7183964953663242\", \"0.8539788722377375\", \"0.8239444528752622\", \"0.7916176207368374\"], \"11\": [\"0.9756097793579102\", \"0.9151657232716784\", \"0.8866428394307877\", \"0.8021404089798435\", \"0.7698366511555069\"], \"12\": [\"0.8602150678634644\", \"0.8208044784812699\", \"0.9643979742488535\", \"1.0\", \"1.0\"], \"13\": [\"0.9142857193946838\", \"1.0\", \"0.9987962920826111\", \"0.9931703249329342\", \"0.9298918574620448\"], \"14\": [\"0.9572649598121643\", \"0.9777604219825083\", \"0.8032522673188167\", \"0.7961315146673383\", \"0.9042605905028186\"], \"15\": [\"0.8723404407501221\", \"0.8709851494586376\", \"0.6967891162596921\", \"0.6517295812764629\", \"0.6125280701743805\"], \"16\": [\"0.976190447807312\", \"1.0\", \"1.0\", \"1.0\", \"0.9059552696508648\"], \"17\": [\"0.7884615659713745\", \"0.7043630550644677\", \"0.7229077021863914\", \"0.5927093692988337\", \"0.7270607767583099\"], \"18\": [\"0.8723404407501221\", \"0.862068838895013\", \"0.8269709765142678\", \"0.8656156891888379\", \"0.9681075499404925\"], \"19\": [\"0.9434523582458496\", \"0.8899209417460925\", \"0.8487447479024821\", \"1.0\", \"0.8721629592302116\"], \"20\": [\"0.8805309534072876\", \"0.8320116365014649\", \"0.882529253790269\", \"0.8538288072289105\", \"0.6972831117927905\"], \"21\": [\"0.975806474685669\", \"1.0\", \"0.9563597638857201\", \"1.0\", \"0.96807231313915\"], \"22\": [\"0.834482729434967\", \"0.8166716034156569\", \"0.9404187943552825\", \"1.0\", \"1.0\"], \"23\": [\"0.8996282815933228\", \"0.7029612217706456\", \"0.7692661089614848\", \"0.8477150138236433\", \"0.8026081133799058\"], \"24\": [\"0.9500638246536255\", \"1.0\", \"1.0\", \"0.9786707018398783\", \"1.0\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2871,9 +2871,9 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8636363744735718\", \"0.92886081112948\", \"1.0\", \"0.8388038334314838\", \"0.8271875657967567\"], \"1\": [\"0.9795918464660645\", \"1.0\", \"0.982543943359856\", \"1.0\", \"1.0\"], \"2\": [\"0.774193525314331\", \"0.8243560838953359\", \"0.995089381881134\", \"1.0\", \"0.9412026289459778\"], \"3\": [\"0.8648648858070374\", \"0.8162655767088807\", \"0.7795336085778017\", \"0.7411887914229585\", \"0.8083397554971863\"], \"4\": [\"0.9410282373428345\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"5\": [\"0.8947368264198303\", \"1.0\", \"1.0\", \"0.9417175273644387\", \"1.0\"], \"6\": [\"0.875\", \"0.8395464300133455\", \"0.7456776102241438\", \"0.7379193629190488\", \"0.7301023910352686\"], \"7\": [\"0.9333333373069763\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"8\": [\"0.9032257795333862\", \"0.8832691274412479\", \"0.898138741685616\", \"0.8053984822297517\", \"0.7001154768020333\"], \"9\": [\"0.9358024001121521\", \"0.723815473128497\", \"0.7624543787388742\", \"0.822502223319343\", \"0.8275619527545803\"], \"10\": [\"0.8861788511276245\", \"0.9405222040176702\", \"0.9577679141433092\", \"0.8603178410811596\", \"0.9197755518663465\"], \"11\": [\"0.9750000238418579\", \"0.8782885107832065\", \"0.8367072960272697\", \"0.7986760129835162\", \"0.9105716497643859\"], \"12\": [\"0.8666666746139526\", \"0.9251160091099873\", \"0.746263327514448\", \"0.8748620924287724\", \"1.0\"], \"13\": [\"0.9176470637321472\", \"0.8991453249174426\", \"1.0\", \"0.9811549933268298\", \"0.9570742194944619\"], \"14\": [\"0.9537037014961243\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"15\": [\"0.9126213788986206\", \"0.95590361651259\", \"0.8577341451663933\", \"0.799358726729822\", \"0.809309780504532\"], \"16\": [\"0.942307710647583\", \"0.9506323824318652\", \"1.0\", \"1.0\", \"1.0\"], \"17\": [\"0.8909090757369995\", \"0.9458597618150345\", \"1.0\", \"1.0\", \"0.9593212131992811\"], \"18\": [\"0.9158878326416016\", \"0.8326578128511968\", \"0.8022102546108545\", \"1.0\", \"0.8879098256031821\"], \"19\": [\"0.9621212482452393\", \"1.0\", \"0.9688050743369877\", \"0.9954941235609506\", \"0.9783148891769534\"], \"20\": [\"0.8982300758361816\", \"0.857543273758781\", \"0.904582479269161\", \"0.9808626574410144\", \"0.8590755384678712\"], \"21\": [\"0.9621211886405945\", \"1.0\", \"1.0\", \"1.0\", \"0.9915753120646987\"], \"22\": [\"0.8758620619773865\", \"1.0\", \"1.0\", \"1.0\", \"0.9595588659073383\"], \"23\": [\"0.916967511177063\", \"0.9251057231160493\", \"0.9417636941765279\", \"1.0\", \"0.8515125521376568\"], \"24\": [\"0.9577693343162537\", \"0.9319297591011309\", \"0.9925472053943316\", \"1.0\", \"0.7621692516448988\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8442623019218445\", \"0.8228368850054627\", \"0.7625017470167952\", \"0.5872114690564066\", \"0.6471566536176281\"], \"1\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"0.9238540508253836\"], \"2\": [\"0.7164179086685181\", \"0.5260483546090627\", \"0.6667243013678141\", \"0.6583806400144895\", \"0.7824903970800032\"], \"3\": [\"0.834782600402832\", \"0.7699832445094515\", \"0.7621212758948609\", \"0.7514016602112257\", \"0.829238844116853\"], \"4\": [\"0.9251017570495605\", \"0.9603802175025565\", \"1.0\", \"1.0\", \"0.9921543953777135\"], \"5\": [\"0.8936170339584351\", \"0.8546169099506077\", \"0.8087788323321982\", \"0.7608500038433639\", \"0.9670667620962246\"], \"6\": [\"0.9583333134651184\", \"0.8308840458434986\", \"0.8016947775667752\", \"0.724680539413762\", \"0.8372601591293443\"], \"7\": [\"0.8518518805503845\", \"0.8134346033673987\", \"0.6379958916526355\", \"0.6576201852361977\", \"0.6569282213102983\"], \"8\": [\"0.9019607901573181\", \"1.0\", \"1.0\", \"1.0\", \"0.8802982536952462\"], \"9\": [\"0.9777777791023254\", \"0.808717328320772\", \"0.8389433885147825\", \"0.6803208424373841\", \"0.515650933392587\"], \"10\": [\"0.8863636255264282\", \"0.7183964953663242\", \"0.8539788722377375\", \"0.8239444528752622\", \"0.7916176207368374\"], \"11\": [\"0.9756097793579102\", \"0.9151657232716784\", \"0.8866428394307877\", \"0.8021404089798435\", \"0.7698366511555069\"], \"12\": [\"0.8602150678634644\", \"0.8208044784812699\", \"0.9643979742488535\", \"1.0\", \"1.0\"], \"13\": [\"0.9142857193946838\", \"1.0\", \"0.9987962920826111\", \"0.9931703249329342\", \"0.9298918574620448\"], \"14\": [\"0.9572649598121643\", \"0.9777604219825083\", \"0.8032522673188167\", \"0.7961315146673383\", \"0.9042605905028186\"], \"15\": [\"0.8723404407501221\", \"0.8709851494586376\", \"0.6967891162596921\", \"0.6517295812764629\", \"0.6125280701743805\"], \"16\": [\"0.976190447807312\", \"1.0\", \"1.0\", \"1.0\", \"0.9059552696508648\"], \"17\": [\"0.7884615659713745\", \"0.7043630550644677\", \"0.7229077021863914\", \"0.5927093692988337\", \"0.7270607767583099\"], \"18\": [\"0.8723404407501221\", \"0.862068838895013\", \"0.8269709765142678\", \"0.8656156891888379\", \"0.9681075499404925\"], \"19\": [\"0.9434523582458496\", \"0.8899209417460925\", \"0.8487447479024821\", \"1.0\", \"0.8721629592302116\"], \"20\": [\"0.8805309534072876\", \"0.8320116365014649\", \"0.882529253790269\", \"0.8538288072289105\", \"0.6972831117927905\"], \"21\": [\"0.975806474685669\", \"1.0\", \"0.9563597638857201\", \"1.0\", \"0.96807231313915\"], \"22\": [\"0.834482729434967\", \"0.8166716034156569\", \"0.9404187943552825\", \"1.0\", \"1.0\"], \"23\": [\"0.8996282815933228\", \"0.7029612217706456\", \"0.7692661089614848\", \"0.8477150138236433\", \"0.8026081133799058\"], \"24\": [\"0.9500638246536255\", \"1.0\", \"1.0\", \"0.9786707018398783\", \"1.0\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); + var passed_all = JSON.parse("{\"0\": false, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": false, \"8\": true, \"9\": false, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": false, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": false, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -3386,7 +3386,7 @@

Ethical Considerations

]; // create global variable for max_n_evals - var histories = JSON.parse("{\"0\": [\"0.8636363744735718\", \"0.92886081112948\", \"1.0\", \"0.8388038334314838\", \"0.8271875657967567\"], \"1\": [\"0.9795918464660645\", \"1.0\", \"0.982543943359856\", \"1.0\", \"1.0\"], \"2\": [\"0.774193525314331\", \"0.8243560838953359\", \"0.995089381881134\", \"1.0\", \"0.9412026289459778\"], \"3\": [\"0.8648648858070374\", \"0.8162655767088807\", \"0.7795336085778017\", \"0.7411887914229585\", \"0.8083397554971863\"], \"4\": [\"0.9410282373428345\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"5\": [\"0.8947368264198303\", \"1.0\", \"1.0\", \"0.9417175273644387\", \"1.0\"], \"6\": [\"0.875\", \"0.8395464300133455\", \"0.7456776102241438\", \"0.7379193629190488\", \"0.7301023910352686\"], \"7\": [\"0.9333333373069763\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"8\": [\"0.9032257795333862\", \"0.8832691274412479\", \"0.898138741685616\", \"0.8053984822297517\", \"0.7001154768020333\"], \"9\": [\"0.9358024001121521\", \"0.723815473128497\", \"0.7624543787388742\", \"0.822502223319343\", \"0.8275619527545803\"], \"10\": [\"0.8861788511276245\", \"0.9405222040176702\", \"0.9577679141433092\", \"0.8603178410811596\", \"0.9197755518663465\"], \"11\": [\"0.9750000238418579\", \"0.8782885107832065\", \"0.8367072960272697\", \"0.7986760129835162\", \"0.9105716497643859\"], \"12\": [\"0.8666666746139526\", \"0.9251160091099873\", \"0.746263327514448\", \"0.8748620924287724\", \"1.0\"], \"13\": [\"0.9176470637321472\", \"0.8991453249174426\", \"1.0\", \"0.9811549933268298\", \"0.9570742194944619\"], \"14\": [\"0.9537037014961243\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"15\": [\"0.9126213788986206\", \"0.95590361651259\", \"0.8577341451663933\", \"0.799358726729822\", \"0.809309780504532\"], \"16\": [\"0.942307710647583\", \"0.9506323824318652\", \"1.0\", \"1.0\", \"1.0\"], \"17\": [\"0.8909090757369995\", \"0.9458597618150345\", \"1.0\", \"1.0\", \"0.9593212131992811\"], \"18\": [\"0.9158878326416016\", \"0.8326578128511968\", \"0.8022102546108545\", \"1.0\", \"0.8879098256031821\"], \"19\": [\"0.9621212482452393\", \"1.0\", \"0.9688050743369877\", \"0.9954941235609506\", \"0.9783148891769534\"], \"20\": [\"0.8982300758361816\", \"0.857543273758781\", \"0.904582479269161\", \"0.9808626574410144\", \"0.8590755384678712\"], \"21\": [\"0.9621211886405945\", \"1.0\", \"1.0\", \"1.0\", \"0.9915753120646987\"], \"22\": [\"0.8758620619773865\", \"1.0\", \"1.0\", \"1.0\", \"0.9595588659073383\"], \"23\": [\"0.916967511177063\", \"0.9251057231160493\", \"0.9417636941765279\", \"1.0\", \"0.8515125521376568\"], \"24\": [\"0.9577693343162537\", \"0.9319297591011309\", \"0.9925472053943316\", \"1.0\", \"0.7621692516448988\"]}"); + var histories = JSON.parse("{\"0\": [\"0.8442623019218445\", \"0.8228368850054627\", \"0.7625017470167952\", \"0.5872114690564066\", \"0.6471566536176281\"], \"1\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"0.9238540508253836\"], \"2\": [\"0.7164179086685181\", \"0.5260483546090627\", \"0.6667243013678141\", \"0.6583806400144895\", \"0.7824903970800032\"], \"3\": [\"0.834782600402832\", \"0.7699832445094515\", \"0.7621212758948609\", \"0.7514016602112257\", \"0.829238844116853\"], \"4\": [\"0.9251017570495605\", \"0.9603802175025565\", \"1.0\", \"1.0\", \"0.9921543953777135\"], \"5\": [\"0.8936170339584351\", \"0.8546169099506077\", \"0.8087788323321982\", \"0.7608500038433639\", \"0.9670667620962246\"], \"6\": [\"0.9583333134651184\", \"0.8308840458434986\", \"0.8016947775667752\", \"0.724680539413762\", \"0.8372601591293443\"], \"7\": [\"0.8518518805503845\", \"0.8134346033673987\", \"0.6379958916526355\", \"0.6576201852361977\", \"0.6569282213102983\"], \"8\": [\"0.9019607901573181\", \"1.0\", \"1.0\", \"1.0\", \"0.8802982536952462\"], \"9\": [\"0.9777777791023254\", \"0.808717328320772\", \"0.8389433885147825\", \"0.6803208424373841\", \"0.515650933392587\"], \"10\": [\"0.8863636255264282\", \"0.7183964953663242\", \"0.8539788722377375\", \"0.8239444528752622\", \"0.7916176207368374\"], \"11\": [\"0.9756097793579102\", \"0.9151657232716784\", \"0.8866428394307877\", \"0.8021404089798435\", \"0.7698366511555069\"], \"12\": [\"0.8602150678634644\", \"0.8208044784812699\", \"0.9643979742488535\", \"1.0\", \"1.0\"], \"13\": [\"0.9142857193946838\", \"1.0\", \"0.9987962920826111\", \"0.9931703249329342\", \"0.9298918574620448\"], \"14\": [\"0.9572649598121643\", \"0.9777604219825083\", \"0.8032522673188167\", \"0.7961315146673383\", \"0.9042605905028186\"], \"15\": [\"0.8723404407501221\", \"0.8709851494586376\", \"0.6967891162596921\", \"0.6517295812764629\", \"0.6125280701743805\"], \"16\": [\"0.976190447807312\", \"1.0\", \"1.0\", \"1.0\", \"0.9059552696508648\"], \"17\": [\"0.7884615659713745\", \"0.7043630550644677\", \"0.7229077021863914\", \"0.5927093692988337\", \"0.7270607767583099\"], \"18\": [\"0.8723404407501221\", \"0.862068838895013\", \"0.8269709765142678\", \"0.8656156891888379\", \"0.9681075499404925\"], \"19\": [\"0.9434523582458496\", \"0.8899209417460925\", \"0.8487447479024821\", \"1.0\", \"0.8721629592302116\"], \"20\": [\"0.8805309534072876\", \"0.8320116365014649\", \"0.882529253790269\", \"0.8538288072289105\", \"0.6972831117927905\"], \"21\": [\"0.975806474685669\", \"1.0\", \"0.9563597638857201\", \"1.0\", \"0.96807231313915\"], \"22\": [\"0.834482729434967\", \"0.8166716034156569\", \"0.9404187943552825\", \"1.0\", \"1.0\"], \"23\": [\"0.8996282815933228\", \"0.7029612217706456\", \"0.7692661089614848\", \"0.8477150138236433\", \"0.8026081133799058\"], \"24\": [\"0.9500638246536255\", \"1.0\", \"1.0\", \"0.9786707018398783\", \"1.0\"]}"); // get max_n_evals from histories var history_data = []; for (let i = 0; i < histories[0].length; i++) { diff --git a/api/tutorials/synthea/los_prediction.html b/api/tutorials/synthea/los_prediction.html index 47a474a70..436a3def9 100644 --- a/api/tutorials/synthea/los_prediction.html +++ b/api/tutorials/synthea/los_prediction.html @@ -566,7 +566,7 @@

Compute length of stay (labels) 
-2024-06-23 18:27:50,616 INFO cycquery.orm    - Database setup, ready to run queries!
+2024-06-24 14:09:09,581 INFO cycquery.orm    - Database setup, ready to run queries!

@@ -574,7 +574,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:17,546 INFO cycquery.orm    - Query returned successfully!
+2024-06-24 14:09:20,355 INFO cycquery.orm    - Query returned successfully!

@@ -582,7 +582,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:17,548 INFO cycquery.utils.profile - Finished executing function run_query in 25.825068 s
+2024-06-24 14:09:20,356 INFO cycquery.utils.profile - Finished executing function run_query in 9.663798 s

@@ -590,7 +590,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:22,581 INFO cycquery.orm    - Query returned successfully!
+2024-06-24 14:09:25,314 INFO cycquery.orm    - Query returned successfully!

@@ -598,7 +598,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:22,583 INFO cycquery.utils.profile - Finished executing function run_query in 5.031993 s
+2024-06-24 14:09:25,316 INFO cycquery.utils.profile - Finished executing function run_query in 4.957239 s

@@ -606,7 +606,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:29,007 INFO cycquery.orm    - Query returned successfully!
+2024-06-24 14:09:29,401 INFO cycquery.orm    - Query returned successfully!

@@ -614,7 +614,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:29,009 INFO cycquery.utils.profile - Finished executing function run_query in 2.417814 s
+2024-06-24 14:09:29,403 INFO cycquery.utils.profile - Finished executing function run_query in 0.324243 s

@@ -622,7 +622,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:31,472 INFO cycquery.orm    - Query returned successfully!
+2024-06-24 14:09:29,794 INFO cycquery.orm    - Query returned successfully!

@@ -630,7 +630,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:31,473 INFO cycquery.utils.profile - Finished executing function run_query in 2.458872 s
+2024-06-24 14:09:29,796 INFO cycquery.utils.profile - Finished executing function run_query in 0.386899 s

@@ -638,7 +638,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:31,659 INFO cycquery.orm    - Query returned successfully!
+2024-06-24 14:09:29,975 INFO cycquery.orm    - Query returned successfully!

@@ -646,7 +646,7 @@

Compute length of stay (labels) 
-2024-06-23 18:28:31,661 INFO cycquery.utils.profile - Finished executing function run_query in 0.185721 s
+2024-06-24 14:09:29,976 INFO cycquery.utils.profile - Finished executing function run_query in 0.179210 s

@@ -699,9 +699,9 @@

Drop NaNs based on the
-
+
@@ -1263,7 +1263,7 @@

Training 
-2024-06-23 18:29:11,730 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
+2024-06-24 14:26:04,349 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
@@ -1271,7 +1271,7 @@

Training 

-2024-06-23 18:29:11,732 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 500
+2024-06-24 14:26:04,353 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 100
@@ -1279,7 +1279,7 @@

Training 

-2024-06-23 18:29:11,734 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
+2024-06-24 14:26:04,354 INFO cyclops.models.wrappers.sk_model - Best max_depth: 2
@@ -1287,7 +1287,7 @@

Training 

-2024-06-23 18:29:11,735 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
+2024-06-24 14:26:04,356 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
@@ -1295,7 +1295,7 @@

Training 

-2024-06-23 18:29:11,736 INFO cyclops.models.wrappers.sk_model - Best gamma: 10
+2024-06-24 14:26:04,357 INFO cyclops.models.wrappers.sk_model - Best gamma: 0
@@ -1303,7 +1303,7 @@

Training 

-2024-06-23 18:29:11,737 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.8
+2024-06-24 14:26:04,358 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.7
@@ -1717,24 +1717,24 @@

Training } 
XGBClassifier(base_score=None, booster=None, callbacks=None,
               colsample_bylevel=None, colsample_bynode=None,
-              colsample_bytree=0.8, early_stopping_rounds=None,
+              colsample_bytree=0.7, early_stopping_rounds=None,
               enable_categorical=False, eval_metric='logloss',
-              feature_types=None, gamma=10, gpu_id=None, grow_policy=None,
+              feature_types=None, gamma=0, gpu_id=None, grow_policy=None,
               importance_type=None, interaction_constraints=None,
               learning_rate=0.1, max_bin=None, max_cat_threshold=None,
-              max_cat_to_onehot=None, max_delta_step=None, max_depth=5,
+              max_cat_to_onehot=None, max_delta_step=None, max_depth=2,
               max_leaves=None, min_child_weight=3, missing=nan,
-              monotone_constraints=None, n_estimators=500, n_jobs=None,
+              monotone_constraints=None, n_estimators=100, n_jobs=None,
               num_parallel_tree=None, predictor=None, random_state=123, ...)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

@@ -1751,7 +1751,7 @@

Training 

-{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.8, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 10, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 500, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}
+{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.7, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 0, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 2, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 100, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}

Log the model parameters to the report.

@@ -1787,7 +1787,7 @@

Prediction
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Evaluation

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Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -2101,9 +2101,9 @@

Evaluation
-

diff --git a/api/tutorials/synthea/los_prediction.ipynb b/api/tutorials/synthea/los_prediction.ipynb index 8331d4fb2..501f273b5 100644 --- a/api/tutorials/synthea/los_prediction.ipynb +++ b/api/tutorials/synthea/los_prediction.ipynb @@ -33,10 +33,10 @@ "id": "53009e6b", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:27:34.109570Z", - "iopub.status.busy": "2024-06-23T22:27:34.108667Z", - "iopub.status.idle": "2024-06-23T22:27:48.963314Z", - "shell.execute_reply": "2024-06-23T22:27:48.961360Z" + "iopub.execute_input": "2024-06-24T18:08:52.734745Z", + "iopub.status.busy": "2024-06-24T18:08:52.733469Z", + "iopub.status.idle": "2024-06-24T18:09:07.984909Z", + "shell.execute_reply": "2024-06-24T18:09:07.982895Z" } }, "outputs": [], @@ -97,10 +97,10 @@ "id": "afae58a8-5708-4e05-8695-25ba3ce1a71f", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:27:48.972068Z", - "iopub.status.busy": "2024-06-23T22:27:48.970838Z", - "iopub.status.idle": "2024-06-23T22:27:48.979041Z", - "shell.execute_reply": "2024-06-23T22:27:48.977476Z" + "iopub.execute_input": "2024-06-24T18:09:07.994317Z", + "iopub.status.busy": "2024-06-24T18:09:07.992448Z", + "iopub.status.idle": "2024-06-24T18:09:08.000836Z", + "shell.execute_reply": "2024-06-24T18:09:07.999236Z" }, "tags": [] }, @@ -123,10 +123,10 @@ "id": "739b109a-011b-4e6e-a3de-964edeffddbd", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:27:48.986038Z", - "iopub.status.busy": "2024-06-23T22:27:48.984780Z", - "iopub.status.idle": "2024-06-23T22:27:48.992227Z", - "shell.execute_reply": "2024-06-23T22:27:48.990685Z" + "iopub.execute_input": "2024-06-24T18:09:08.007746Z", + "iopub.status.busy": "2024-06-24T18:09:08.006794Z", + "iopub.status.idle": "2024-06-24T18:09:08.014289Z", + "shell.execute_reply": "2024-06-24T18:09:08.012654Z" }, "tags": [] }, @@ -157,10 +157,10 @@ "id": "e497df9f-0f3d-4e9c-845c-539627a37f67", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:27:48.999018Z", - "iopub.status.busy": "2024-06-23T22:27:48.998444Z", - "iopub.status.idle": "2024-06-23T22:28:31.768197Z", - "shell.execute_reply": "2024-06-23T22:28:31.766226Z" + "iopub.execute_input": "2024-06-24T18:09:08.021507Z", + "iopub.status.busy": "2024-06-24T18:09:08.020471Z", + "iopub.status.idle": "2024-06-24T18:09:30.053949Z", + "shell.execute_reply": "2024-06-24T18:09:30.052283Z" }, "tags": [] }, @@ -169,77 +169,77 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:27:50,616 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" + "2024-06-24 14:09:09,581 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:17,546 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-06-24 14:09:20,355 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:17,548 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 25.825068 s\n" + "2024-06-24 14:09:20,356 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 9.663798 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:22,581 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-06-24 14:09:25,314 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:22,583 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 5.031993 s\n" + "2024-06-24 14:09:25,316 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 4.957239 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:29,007 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-06-24 14:09:29,401 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:29,009 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 2.417814 s\n" + "2024-06-24 14:09:29,403 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.324243 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:31,472 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-06-24 14:09:29,794 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:31,473 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 2.458872 s\n" + "2024-06-24 14:09:29,796 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.386899 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:31,659 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-06-24 14:09:29,975 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-06-23 18:28:31,661 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.185721 s\n" + "2024-06-24 14:09:29,976 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.179210 s\n" ] } ], @@ -398,10 +398,10 @@ "id": "c576ee51-e825-4970-86e8-3e5f221f145c", "metadata": { "execution": { - "iopub.execute_input": "2024-06-23T22:28:31.776637Z", - "iopub.status.busy": "2024-06-23T22:28:31.775485Z", - "iopub.status.idle": "2024-06-23T22:28:31.985858Z", - "shell.execute_reply": "2024-06-23T22:28:31.984090Z" + "iopub.execute_input": "2024-06-24T18:09:30.061690Z", + "iopub.status.busy": "2024-06-24T18:09:30.060292Z", + "iopub.status.idle": "2024-06-24T18:09:30.268448Z", + "shell.execute_reply": "2024-06-24T18:09:30.266782Z" }, "tags": [] }, @@ -1497,9 +1497,9 @@ } }, "text/html": [ - "
- + +

CyclOps 0.2.0 release

· 4 min read
Carolyn Chong
Amrit Krishnan
diff --git a/blog/archive/index.html b/blog/archive/index.html index a1809ad5b..2d2f4eb77 100644 --- a/blog/archive/index.html +++ b/blog/archive/index.html @@ -5,8 +5,8 @@ Archive | CyclOps - - + +

Archive

Archive

2023​

diff --git a/blog/index.html b/blog/index.html index 00f5fd17e..b91951848 100644 --- a/blog/index.html +++ b/blog/index.html @@ -5,8 +5,8 @@ Blog | CyclOps - - + +

· 4 min read
Carolyn Chong
Amrit Krishnan
diff --git a/blog/tags/0-2-0/index.html b/blog/tags/0-2-0/index.html index 8f8640874..3d1f79c36 100644 --- a/blog/tags/0-2-0/index.html +++ b/blog/tags/0-2-0/index.html @@ -5,8 +5,8 @@ One post tagged with "0.2.0" | CyclOps - - + +

One post tagged with "0.2.0"

View All Tags

· 4 min read
Carolyn Chong
Amrit Krishnan
diff --git a/blog/tags/index.html b/blog/tags/index.html index 6676ce496..bf8a403ff 100644 --- a/blog/tags/index.html +++ b/blog/tags/index.html @@ -5,8 +5,8 @@ Tags | CyclOps - - + +

Tags

diff --git a/docs/intro/index.html b/docs/intro/index.html index 4b48cb1a6..f4f2c5f6f 100644 --- a/docs/intro/index.html +++ b/docs/intro/index.html @@ -5,8 +5,8 @@ intro | CyclOps - - + +

intro

Getting Started​

diff --git a/index.html b/index.html index e7a2f4008..bde056398 100644 --- a/index.html +++ b/index.html @@ -5,8 +5,8 @@ CyclOps | CyclOps - - + +

CyclOps

Cyclical development towards Operationalizing ML models for healthcare

Rigorous Evaluation

CyclOps APIs support rigorous evaluation across patient sub-populations

Monitoring

CyclOps supports monitoring of clinical ML models for performance degradation

diff --git a/markdown-page/index.html b/markdown-page/index.html index 6d4833ecd..27e007b41 100644 --- a/markdown-page/index.html +++ b/markdown-page/index.html @@ -5,8 +5,8 @@ Markdown page example | CyclOps - - + +

Markdown page example