Rename processes according to recent discussions from #396

CHANGELOG.md

@@ -15,8 +15,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
     - `load_geojson`
     - `load_ml_model`
     - `load_url`
-    - `predict_ml_model`
-    - `predict_ml_model_probabilities`
+    - `ml_fit_class_random_forest`
+    - `ml_fit_regr_random_forest`
+    - `ml_predict`
+    - `ml_predict_probabilities`
     - `save_ml_model`
     - `unflatten_dimension`
     - `vector_buffer`

proposals/predict_dl_model.json → proposals/dl_predict.json

@@ -1,6 +1,6 @@
 {
-    "id": "predict_dl_model",
-    "summary": "Predict values values using DL",
+    "id": "dl_predict",
+    "summary": "Predict classification or regression values using DL",
     "description": "Applies a machine learning model to a data cube of input features and predicts output values or classes for it. This process can be used as process in ``apply_neighborhood()`` to specify the patch size and overlap.",
     "categories": [
         "deep learning",

proposals/load_ml_model.json

@@ -1,7 +1,7 @@
 {
     "id": "load_ml_model",
     "summary": "Load a ML model",
-    "description": "Loads a machine learning model from a STAC Item.\n\nSuch a model could be trained and saved as part of a previous batch job with processes such as  ``fit_regr_random_forest()`` and ``save_ml_model()``.",
+    "description": "Loads a machine learning model from a STAC Item.\n\nSuch a model could be trained and saved as part of a previous batch job with processes such as  ``ml_fit_regr_random_forest()`` and ``save_ml_model()``.",
     "categories": [
         "machine learning",
         "import"
@@ -29,7 +29,7 @@
         }
     ],
     "returns": {
-        "description": "A machine learning model to be used with machine learning processes such as ``predict_ml_model()`` or ``predict_ml_model_probabilities()``.",
+        "description": "A machine learning model to be used with machine learning processes such as ``ml_predict()`` or ``ml_predict_probabilities()``.",
         "schema": {
             "type": "object",
             "subtype": "ml-model"

proposals/fit_class_random_forest.json → proposals/ml_fit_class_random_forest.json

@@ -1,5 +1,5 @@
 {
-    "id": "fit_class_random_forest",
+    "id": "ml_fit_class_random_forest",
     "summary": "Train a random forest classification model",
     "description": "Executes the fit of a random forest classification based on training data. The process does not include a separate split of the data in test, validation and training data. The Random Forest classification model is based on the approach by Breiman (2001).",
     "categories": [

proposals/fit_regr_random_forest.json → proposals/ml_fit_regr_random_forest.json

@@ -1,5 +1,5 @@
 {
-    "id": "fit_regr_random_forest",
+    "id": "ml_fit_regr_random_forest",
     "summary": "Train a random forest regression model",
     "description": "Executes the fit of a random forest regression based on training data. The process does not include a separate split of the data in test, validation and training data. The Random Forest regression model is based on the approach by Breiman (2001).",
     "categories": [

proposals/predict_ml_model.json → proposals/ml_predict.json

@@ -1,5 +1,5 @@
 {
-    "id": "predict_ml_model",
+    "id": "ml_predict",
     "summary": "Predict classification or regression values using ML",
     "description": "Applies a machine learning model to a data cube of input features and predicts output values or classes for it.",
     "categories": [
@@ -17,7 +17,7 @@
         },
         {
             "name": "model",
-            "description": "A ML model that was trained with one of the ML training processes such as ``fit_class_random_forest()``.",
+            "description": "A ML model that was trained with one of the ML training processes such as ``ml_fit_class_random_forest()``.",
             "schema": {
                 "type": "object",
                 "subtype": "ml-model"

proposals/predict_ml_model_probabilities.json → proposals/ml_predict_probabilities.json

@@ -1,5 +1,5 @@
 {
-    "id": "predict_ml_model_probabilities",
+    "id": "ml_predict_probabilities",
     "summary": "Predict class probabilities using ML",
     "description": "Applies a machine learning model to a data cube of input features and predicts the probabilities of the output classes.",
     "categories": [
@@ -17,7 +17,7 @@
         },
         {
             "name": "model",
-            "description": "A ML model that was trained with one of the ML training processes such as ``fit_regr_random_forest()``.",
+            "description": "A ML model that was trained with one of the ML training processes such as ``ml_fit_regr_random_forest()``.",
             "schema": {
                 "type": "object",
                 "subtype": "ml-model"