diff --git a/Chapter2-DataManipulation/2.10_dimensionality_reduction.html b/Chapter2-DataManipulation/2.10_dimensionality_reduction.html index 8a740a1..56fe74d 100644 --- a/Chapter2-DataManipulation/2.10_dimensionality_reduction.html +++ b/Chapter2-DataManipulation/2.10_dimensionality_reduction.html @@ -908,7 +908,7 @@

2.10.1 Feature selection via parameter exploration
-
<matplotlib.legend.Legend at 0x7f5a372da3e0>
+
<matplotlib.legend.Legend at 0x7f60f04a8fa0>
 

 

 ../_images/2.10_dimensionality_reduction_4_1.png
@@ -989,8 +989,16 @@ 
Step one: subtract the mean
## Remove the mean of the data
 Xavg = np.mean(X, axis=1)                 # Compute mean
 B = X - np.tile(Xavg,(nPoints,1)).T       # Mean-subtracted data
+
+plt.scatter(B[0,:],B[1,:], color='k', alpha=0.125)
+

+
+
+
+
<matplotlib.collections.PathCollection at 0x7f60ecda71c0>
+../_images/2.10_dimensionality_reduction_12_1.png
@@ -1006,21 +1014,6 @@

Step two: Determine the SVD of the covariance matrix -
[[ 0.42469643  0.747179    0.85328813 ...  0.88246352 -1.884191
-  -1.32403592]
- [-0.18730514  0.80047482  1.11341706 ... -0.09048239 -2.95497644
-  -0.18146037]]
-[[ 0.42469643 -0.18730514]
- [ 0.747179    0.80047482]
- [ 0.85328813  1.11341706]
- ...
- [ 0.88246352 -0.09048239]
- [-1.884191   -2.95497644]
- [-1.32403592 -0.18146037]]
-
-
-
@@ -1198,7 +1191,7 @@

2.10.3 PCA on 3D data. -
<matplotlib.legend.Legend at 0x7f1890190820>
+
<matplotlib.legend.Legend at 0x7f60ec163730>
 

 

 ../_images/2.10_dimensionality_reduction_25_1.png
@@ -1304,7 +1297,7 @@ 
2.10.3 PCA on 3D data.
-
minimum dimension size to explain 95% of the variance:  1
+
Minimum dimension size to explain 95% of the variance:  1
 

 

 

@@ -1344,10 +1337,6 @@ 
2.10.3 PCA on 3D data.
-
[ 1.69  -0.668 -6.747]
-[ 2.14194643 -1.44586065 -6.42108578]
-

-

SVD can be computationally intensive for larger dimensions.

diff --git a/Chapter3-MachineLearning/3.3_binary_classification.html b/Chapter3-MachineLearning/3.3_binary_classification.html index 7092d9b..7070101 100644 --- a/Chapter3-MachineLearning/3.3_binary_classification.html +++ b/Chapter3-MachineLearning/3.3_binary_classification.html @@ -747,16 +747,10 @@

1.1 Synthetic Data -
---------------------------------------------------------------------------
-ImportError                               Traceback (most recent call last)
-Cell In [7], line 1
-----> 1 from sklearn.inspection import DecisionBoundaryDisplay
-      2 ax = plt.subplot()
-      3 # plot the decision boundary as a background
-
-ImportError: cannot import name 'DecisionBoundaryDisplay' from 'sklearn.inspection' (/Users/marinedenolle/opt/miniconda3/envs/mlgeo_sk/lib/python3.9/site-packages/sklearn/inspection/__init__.py)
+
<matplotlib.collections.PathCollection at 0x7f7c5ef8fdf0>
 

 

+../_images/3.3_binary_classification_8_1.png

The results shows a not-too bad classification, but a low confidence.

@@ -779,11 +773,6 @@

1.1 Synthetic Data# calculate the mean accuracy on the given test data and labels. score = clf.score(X_test, y_test) print("The mean accuracy on the given test and labels is %f" %score) - -# plot the decision boundary as a background -ax = plt.subplot() -# DecisionBoundaryDisplay.from_estimator(clf, X, cmap='PiYG', alpha=0.8, ax=ax, eps=0.5) -ax.scatter(X[:, 0], X[:, 1], c=y, cmap='PiYG', alpha=0.6, edgecolors="k")

@@ -791,68 +780,44 @@

1.1 Synthetic Data
The mean accuracy on the given test and labels is 0.975000
-
<matplotlib.collections.PathCollection at 0x151ada520>
+
<matplotlib.collections.PathCollection at 0x7f7c5ad06230>
 

 

 ../_images/3.3_binary_classification_10_2.png
-

Now we will test the effect of data normalization before the classification. We will stretch the first axis of the data to see the effects.

-
-
-
# make a data set
-X, y = make_moons(noise=0.3, random_state=0)
-X[:,0] = 10*X[:,0] 
-
-
-
-
-
# define ML
-K = 5
-clf= KNeighborsClassifier(K)
-
-# normalize data.
-# X = StandardScaler().fit_transform(X)
-
-# split data between train and test set.
-X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42)
-
-# Fit the model.
-clf.fit(X_train, y_train)
-
-# calculate the mean accuracy on the given test data and labels.
-score = clf.score(X_test, y_test)
-print("The mean accuracy on the given test and labels is %f" %score)
-
-# plot the decision boundary as a background
+
# plot the decision boundary as a background
 ax = plt.subplot()
-# DecisionBoundaryDisplay.from_estimator(clf, X, cmap='PiYG', alpha=0.8, ax=ax, eps=0.5)
+DecisionBoundaryDisplay.from_estimator(clf, X, cmap='PiYG', alpha=0.8, ax=ax, eps=0.5)
 ax.scatter(X[:, 0], X[:, 1], c=y, cmap='PiYG', alpha=0.6, edgecolors="k")
-
The mean accuracy on the given test and labels is 0.775000
+
<matplotlib.collections.PathCollection at 0x7f7c5ab6c760>
 

 

-
<matplotlib.collections.PathCollection at 0x151ada670>
+../_images/3.3_binary_classification_11_1.png
+

+

+
Now we will test to see what happens when you do not normalize your data before the classification. We will stretch the first axis of the data to see the effects.

+

+

+
# make a data set
+X, y = make_moons(noise=0.3, random_state=0)
+X[:,0] = 10*X[:,0] 
 

 

-../_images/3.3_binary_classification_13_2.png
 

 

-
This drastically reduces the performance.

 

 

 
# define ML
 K = 5
 clf= KNeighborsClassifier(K)
 
-# normalize data.
-X = StandardScaler().fit_transform(X)
-
 # split data between train and test set.
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42)
 
@@ -871,19 +836,20 @@ 
1.1 Synthetic Data
-
The mean accuracy on the given test and labels is 0.975000
+
The mean accuracy on the given test and labels is 0.775000
 

 

-
<matplotlib.collections.PathCollection at 0x151aa9100>
+
<matplotlib.collections.PathCollection at 0x7f7c5ace6590>
 

 

-../_images/3.3_binary_classification_15_2.png
+../_images/3.3_binary_classification_14_2.png
 

 

+
This drastically reduces the performance.

2. Classifier Performance Metrics#

-

In a binary classifier, we label one of the two classes as positive, the other class is negative. Let’s consider N data samples.

+

In a binary classifier, we label one of the two classes as positive, the other class as negative. Let’s consider N data samples.

@@ -922,10 +888,10 @@

2. Classifier Performance Metrics\(err = \frac{FP+FN}{N}\) -> 0

-

  • accuracy: the fraction of the data that was correctly classified:

    +

  • Accuracy: the fraction of the data that was correctly classified:

    \(acc = \frac{TP+TN}{N} = 1 - err \) –> 1

  • TP-rate: the ratio of samples predicted in the positive class that are correctly classified:

    diff --git a/Chapter3-MachineLearning/3.4_multiclass_classification.html b/Chapter3-MachineLearning/3.4_multiclass_classification.html index 61a87e0..54f8aae 100644 --- a/Chapter3-MachineLearning/3.4_multiclass_classification.html +++ b/Chapter3-MachineLearning/3.4_multiclass_classification.html @@ -658,42 +658,59 @@

    3.4 Multiclass Classification
    -
    import numpy as np
+
    import numpy as np
 from sklearn.datasets import load_digits,fetch_openml
+from sklearn.metrics import ConfusionMatrixDisplay
 digits = load_digits()
 digits.keys()
    +
    +
    dict_keys(['data', 'target', 'frame', 'feature_names', 'target_names', 'images', 'DESCR'])
+
    +
    +

    The data is vector of floats. The target is an integer that is the attribute of the data. How are the data balanced between the classes? How many samples are there per class?

    -
    # explore data type
+
    # explore data type
 data,y = digits["data"].copy(),digits["target"].copy()
 print(type(data[0][:]),type(y[0]))
 # note that we do not modify the raw data that is stored on the digits dictionary.
    +
    +
    <class 'numpy.ndarray'> <class 'numpy.int64'>
+
    +
    +

    how many classes are there? Since the classes are integers, we can count the number of classes using the function “unique”

    -
    Nclasses = len(np.unique(y))
+
    Nclasses = len(np.unique(y))
 print(np.unique(y))
 print(Nclasses)
    +
    +
    [0 1 2 3 4 5 6 7 8 9]
+10
+
    +
    +

    3.1 Data preparation#

    First print and plot the data.

    -
    # plot the data
+
    # plot the data
 import matplotlib.pyplot as plt
 # plot the first 4 data and their labels.
 _, axes = plt.subplots(nrows=1, ncols=4, figsize=(10, 3))
@@ -704,6 +721,9 @@ 
    3.1 Data preparation
+../_images/3.4_multiclass_classification_7_0.png
+
    @@ -713,7 +733,7 @@

    3.2 Data re-scalinghere

    -
    print(min(data[0]),max(data[0]))
+
    print(min(data[0]),max(data[0]))
 from sklearn.preprocessing import MinMaxScaler
 scaler = MinMaxScaler()
 scaler.fit_transform(data)# fit the model for data normalization
@@ -723,13 +743,26 @@ 
    3.2 Data re-scaling
+
    0.0 15.0
+<class 'numpy.ndarray'>
+[[0.     0.     0.3125 ... 0.     0.     0.    ]
+ [0.     0.     0.     ... 0.625  0.     0.    ]
+ [0.     0.     0.     ... 1.     0.5625 0.    ]
+ ...
+ [0.     0.     0.0625 ... 0.375  0.     0.    ]
+ [0.     0.     0.125  ... 0.75   0.     0.    ]
+ [0.     0.     0.625  ... 0.75   0.0625 0.    ]]
+
    
+
    
+

    3.3 Train-test split#

    -
    # Split data into 50% train and 50% test subsets
+
    # Split data into 50% train and 50% test subsets
 from sklearn.model_selection import train_test_split
 print(f"There are {data.shape[0]} data samples")
 X_train, X_test, y_train, y_test = train_test_split(
@@ -737,10 +770,15 @@ 
    3.3 Train-test split
+
    There are 1797 data samples
+
    
+
    
+
    
 
    
 
    
 
    
-
    import sklearn
+
    import sklearn
 from sklearn import metrics
 from sklearn.svm import SVC
 from sklearn.neighbors import KNeighborsClassifier
@@ -766,10 +804,21 @@ 
    3.3 Train-test split
+
    SVC Accuracy: 0.9688542825361512
+K-nearest Neighbors Accuracy: 0.9555061179087876
+Random Forest Accuracy: 0.92880978865406
+
    
+
    
+
    [Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    0.1s
+[Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    0.0s
+
    
+
    
+
    
 
    
 
    
 
    
-
    _, axes = plt.subplots(nrows=1, ncols=4, figsize=(10, 3))
+
    _, axes = plt.subplots(nrows=1, ncols=4, figsize=(10, 3))
 for ax, image, prediction in zip(axes, X_test, rf_prediction):
     ax.set_axis_off()
     image = image.reshape(8, 8)
@@ -778,57 +827,132 @@ 
    3.3 Train-test split
+../_images/3.4_multiclass_classification_13_0.png
+
    
 
    
 
    
 
    
-
    print("Support Vector Machine")
+
    print("Support Vector Machine")
 print(f"Classification report for classifier {clf}:\n"
       f"{metrics.classification_report(y_test, svc_prediction)}\n")
-disp = metrics.plot_confusion_matrix(clf, X_test, y_test)
+
+disp = ConfusionMatrixDisplay.from_estimator(clf, X_test, y_test)
 disp.figure_.suptitle("Confusion Matrix")
-print(f"Confusion matrix:\n{disp.confusion_matrix}")
+# print(f"Confusion matrix:\n{disp.confusion_matrix}")
 plt.show()
 
    
 
    
 
    
+
    
+
    Support Vector Machine
+Classification report for classifier SVC(gamma=0.001):
+              precision    recall  f1-score   support
+
+           0       1.00      0.99      0.99        88
+           1       0.99      0.97      0.98        91
+           2       0.99      0.99      0.99        86
+           3       0.98      0.87      0.92        91
+           4       0.99      0.96      0.97        92
+           5       0.95      0.97      0.96        91
+           6       0.99      0.99      0.99        91
+           7       0.96      0.99      0.97        89
+           8       0.94      1.00      0.97        88
+           9       0.93      0.98      0.95        92
+
+    accuracy                           0.97       899
+   macro avg       0.97      0.97      0.97       899
+weighted avg       0.97      0.97      0.97       899
+
    
+
    
+../_images/3.4_multiclass_classification_14_1.png
+
    
 
    
 
    
 
    
-
    print("K-nearest neighbors")
+
    print("K-nearest neighbors")
 print(f"Classification report for classifier {knn_clf}:\n"
       f"{metrics.classification_report(y_test, knn_prediction)}\n")
-disp = metrics.plot_confusion_matrix(knn_clf, X_test, y_test)
+disp = ConfusionMatrixDisplay.from_estimator(knn_clf, X_test, y_test)
 disp.figure_.suptitle("Confusion Matrix")
-print(f"Confusion matrix:\n{disp.confusion_matrix}")
+# print(f"Confusion matrix:\n{disp.confusion_matrix}")
 plt.show()
 
    
 
    
 
    
+
    
+
    K-nearest neighbors
+Classification report for classifier KNeighborsClassifier():
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      0.99        88
+           1       0.95      0.98      0.96        91
+           2       0.98      0.93      0.95        86
+           3       0.89      0.90      0.90        91
+           4       1.00      0.95      0.97        92
+           5       0.96      0.98      0.97        91
+           6       0.99      1.00      0.99        91
+           7       0.95      1.00      0.97        89
+           8       0.95      0.90      0.92        88
+           9       0.91      0.92      0.92        92
+
+    accuracy                           0.96       899
+   macro avg       0.96      0.96      0.96       899
+weighted avg       0.96      0.96      0.96       899
+
    
+
    
+../_images/3.4_multiclass_classification_15_1.png
+
    
 
    
 
    
 
    
-
    print("Random Forest")
+
    print("Random Forest")
 print(f"Classification report for classifier {rf_clf}:\n"
       f"{metrics.classification_report(y_test, rf_prediction)}\n")
-disp = metrics.plot_confusion_matrix(rf_clf, X_test, y_test)
+disp = ConfusionMatrixDisplay.from_estimator(rf_clf, X_test, y_test)
 disp.figure_.suptitle("Confusion Matrix")
-print(f"Confusion matrix:\n{disp.confusion_matrix}")
+# print(f"Confusion matrix:\n{disp.confusion_matrix}")
 plt.show()
 
    
 
    
 
    
+
    
+
    Random Forest
+Classification report for classifier RandomForestClassifier(random_state=42, verbose=True):
+              precision    recall  f1-score   support
+
+           0       0.97      0.99      0.98        88
+           1       0.95      0.89      0.92        91
+           2       1.00      0.90      0.94        86
+           3       0.87      0.84      0.85        91
+           4       0.99      0.91      0.95        92
+           5       0.91      0.96      0.93        91
+           6       0.98      1.00      0.99        91
+           7       0.93      0.98      0.95        89
+           8       0.88      0.90      0.89        88
+           9       0.84      0.93      0.89        92
+
+    accuracy                           0.93       899
+   macro avg       0.93      0.93      0.93       899
+weighted avg       0.93      0.93      0.93       899
+
    
+
    
+
    [Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    0.0s
+
    
+
    
+../_images/3.4_multiclass_classification_16_2.png
+
    
 
    
 
    
 
    
-
    from sklearn.metrics import roc_curve,roc_auc_score, precision_recall_curve, RocCurveDisplay, PrecisionRecallDisplay
+
    from sklearn.metrics import roc_curve,roc_auc_score, precision_recall_curve, RocCurveDisplay, PrecisionRecallDisplay
 
    
 
    
 
    
 
    
 
    
 
    
-
    
-from sklearn.multiclass import OneVsRestClassifier
+
    from sklearn.multiclass import OneVsRestClassifier
 from sklearn.preprocessing import label_binarize
 from sklearn import svm
 
@@ -870,11 +994,144 @@ 
    3.3 Train-test split
+
    <matplotlib.legend.Legend at 0x7fd65cb311b0>
+
    
+
    
+../_images/3.4_multiclass_classification_18_1.png
+
    
 
    
 
    
 
    
-
    from sklearn.model_selection import cross_val_predict
-y_train_pred = cross_val_predict(clf,X_train,y_train,cv=3) # predict using K-fold cross validation
+
    from sklearn.model_selection import cross_val_predict
+y_train_pred = cross_val_predict(clf, X_train, y_train, cv=3) # predict using K-fold cross validation
+
    
+
    
+
    
+
    
+
    ---------------------------------------------------------------------------
+ValueError                                Traceback (most recent call last)
+/workspaces/mlgeo-instructor/book/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb Cell 20 line 2
+      <a href='vscode-notebook-cell://codespaces%2Bcurly-winner-7647wqr96rhr49q/workspaces/mlgeo-instructor/book/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb#X25sdnNjb2RlLXJlbW90ZQ%3D%3D?line=0'>1</a> from sklearn.model_selection import cross_val_predict
+----> <a href='vscode-notebook-cell://codespaces%2Bcurly-winner-7647wqr96rhr49q/workspaces/mlgeo-instructor/book/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb#X25sdnNjb2RlLXJlbW90ZQ%3D%3D?line=1'>2</a> y_train_pred = cross_val_predict(clf,X_train,y_train,cv=3) # predict using K-fold cross validation
+
+File ~/.local/lib/python3.10/site-packages/sklearn/model_selection/_validation.py:1033, in cross_val_predict(estimator, X, y, groups, cv, n_jobs, verbose, fit_params, pre_dispatch, method)
+   1030 # We clone the estimator to make sure that all the folds are
+   1031 # independent, and that it is pickle-able.
+   1032 parallel = Parallel(n_jobs=n_jobs, verbose=verbose, pre_dispatch=pre_dispatch)
+-> 1033 predictions = parallel(
+   1034     delayed(_fit_and_predict)(
+   1035         clone(estimator), X, y, train, test, verbose, fit_params, method
+   1036     )
+   1037     for train, test in splits
+   1038 )
+   1040 inv_test_indices = np.empty(len(test_indices), dtype=int)
+   1041 inv_test_indices[test_indices] = np.arange(len(test_indices))
+
+File ~/.local/lib/python3.10/site-packages/sklearn/utils/parallel.py:65, in Parallel.__call__(self, iterable)
+     60 config = get_config()
+     61 iterable_with_config = (
+     62     (_with_config(delayed_func, config), args, kwargs)
+     63     for delayed_func, args, kwargs in iterable
+     64 )
+---> 65 return super().__call__(iterable_with_config)
+
+File ~/.local/lib/python3.10/site-packages/joblib/parallel.py:1863, in Parallel.__call__(self, iterable)
+   1861     output = self._get_sequential_output(iterable)
+   1862     next(output)
+-> 1863     return output if self.return_generator else list(output)
+   1865 # Let's create an ID that uniquely identifies the current call. If the
+   1866 # call is interrupted early and that the same instance is immediately
+   1867 # re-used, this id will be used to prevent workers that were
+   1868 # concurrently finalizing a task from the previous call to run the
+   1869 # callback.
+   1870 with self._lock:
+
+File ~/.local/lib/python3.10/site-packages/joblib/parallel.py:1792, in Parallel._get_sequential_output(self, iterable)
+   1790 self.n_dispatched_batches += 1
+   1791 self.n_dispatched_tasks += 1
+-> 1792 res = func(*args, **kwargs)
+   1793 self.n_completed_tasks += 1
+   1794 self.print_progress()
+
+File ~/.local/lib/python3.10/site-packages/sklearn/utils/parallel.py:127, in _FuncWrapper.__call__(self, *args, **kwargs)
+    125     config = {}
+    126 with config_context(**config):
+--> 127     return self.function(*args, **kwargs)
+
+File ~/.local/lib/python3.10/site-packages/sklearn/model_selection/_validation.py:1115, in _fit_and_predict(estimator, X, y, train, test, verbose, fit_params, method)
+   1113     estimator.fit(X_train, **fit_params)
+   1114 else:
+-> 1115     estimator.fit(X_train, y_train, **fit_params)
+   1116 func = getattr(estimator, method)
+   1117 predictions = func(X_test)
+
+File ~/.local/lib/python3.10/site-packages/sklearn/base.py:1152, in _fit_context.<locals>.decorator.<locals>.wrapper(estimator, *args, **kwargs)
+   1145     estimator._validate_params()
+   1147 with config_context(
+   1148     skip_parameter_validation=(
+   1149         prefer_skip_nested_validation or global_skip_validation
+   1150     )
+   1151 ):
+-> 1152     return fit_method(estimator, *args, **kwargs)
+
+File ~/.local/lib/python3.10/site-packages/sklearn/svm/_base.py:190, in BaseLibSVM.fit(self, X, y, sample_weight)
+    188     check_consistent_length(X, y)
+    189 else:
+--> 190     X, y = self._validate_data(
+    191         X,
+    192         y,
+    193         dtype=np.float64,
+    194         order="C",
+    195         accept_sparse="csr",
+    196         accept_large_sparse=False,
+    197     )
+    199 y = self._validate_targets(y)
+    201 sample_weight = np.asarray(
+    202     [] if sample_weight is None else sample_weight, dtype=np.float64
+    203 )
+
+File ~/.local/lib/python3.10/site-packages/sklearn/base.py:622, in BaseEstimator._validate_data(self, X, y, reset, validate_separately, cast_to_ndarray, **check_params)
+    620         y = check_array(y, input_name="y", **check_y_params)
+    621     else:
+--> 622         X, y = check_X_y(X, y, **check_params)
+    623     out = X, y
+    625 if not no_val_X and check_params.get("ensure_2d", True):
+
+File ~/.local/lib/python3.10/site-packages/sklearn/utils/validation.py:1162, in check_X_y(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)
+   1142     raise ValueError(
+   1143         f"{estimator_name} requires y to be passed, but the target y is None"
+   1144     )
+   1146 X = check_array(
+   1147     X,
+   1148     accept_sparse=accept_sparse,
+   (...)
+   1159     input_name="X",
+   1160 )
+-> 1162 y = _check_y(y, multi_output=multi_output, y_numeric=y_numeric, estimator=estimator)
+   1164 check_consistent_length(X, y)
+   1166 return X, y
+
+File ~/.local/lib/python3.10/site-packages/sklearn/utils/validation.py:1183, in _check_y(y, multi_output, y_numeric, estimator)
+   1181 else:
+   1182     estimator_name = _check_estimator_name(estimator)
+-> 1183     y = column_or_1d(y, warn=True)
+   1184     _assert_all_finite(y, input_name="y", estimator_name=estimator_name)
+   1185     _ensure_no_complex_data(y)
+
+File ~/.local/lib/python3.10/site-packages/sklearn/utils/validation.py:1244, in column_or_1d(y, dtype, warn)
+   1233         warnings.warn(
+   1234             (
+   1235                 "A column-vector y was passed when a 1d array was"
+   (...)
+   1240             stacklevel=2,
+   1241         )
+   1242     return _asarray_with_order(xp.reshape(y, (-1,)), order="C", xp=xp)
+-> 1244 raise ValueError(
+   1245     "y should be a 1d array, got an array of shape {} instead.".format(shape)
+   1246 )
+
+ValueError: y should be a 1d array, got an array of shape (598, 10) instead.
 
    
 
    
 
    
diff --git a/_images/2.10_dimensionality_reduction_10_0.png b/_images/2.10_dimensionality_reduction_10_0.png
index 595e2b3..a74390c 100644
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diff --git a/_images/2.10_dimensionality_reduction_12_1.png b/_images/2.10_dimensionality_reduction_12_1.png
new file mode 100644
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diff --git a/_images/3.3_binary_classification_10_2.png b/_images/3.3_binary_classification_10_2.png
index 34a7f6f..7eb4937 100644
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diff --git a/_images/3.3_binary_classification_11_1.png b/_images/3.3_binary_classification_11_1.png
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diff --git a/_images/3.3_binary_classification_13_2.png b/_images/3.3_binary_classification_14_2.png
similarity index 99%
rename from _images/3.3_binary_classification_13_2.png
rename to _images/3.3_binary_classification_14_2.png
index d174aeb..f5fa6ea 100644
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diff --git a/_images/3.3_binary_classification_15_2.png b/_images/3.3_binary_classification_15_2.png
deleted file mode 100644
index 34a7f6f..0000000
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diff --git a/_images/3.3_binary_classification_5_0.png b/_images/3.3_binary_classification_5_0.png
index 17c6c27..5d0efde 100644
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diff --git a/_images/3.3_binary_classification_8_1.png b/_images/3.3_binary_classification_8_1.png
new file mode 100644
index 0000000..1d69424
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diff --git a/_images/3.4_multiclass_classification_13_0.png b/_images/3.4_multiclass_classification_13_0.png
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index 0000000..74a6297
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diff --git a/_images/3.4_multiclass_classification_14_1.png b/_images/3.4_multiclass_classification_14_1.png
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index 0000000..1bdbccd
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index 0000000..13cee52
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diff --git a/_images/3.4_multiclass_classification_16_2.png b/_images/3.4_multiclass_classification_16_2.png
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diff --git a/_images/3.4_multiclass_classification_18_1.png b/_images/3.4_multiclass_classification_18_1.png
new file mode 100644
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diff --git a/_images/3.4_multiclass_classification_7_0.png b/_images/3.4_multiclass_classification_7_0.png
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diff --git a/_sources/Chapter2-DataManipulation/2.10_dimensionality_reduction.ipynb b/_sources/Chapter2-DataManipulation/2.10_dimensionality_reduction.ipynb
index e9b02c8..9b41d83 100644
--- a/_sources/Chapter2-DataManipulation/2.10_dimensionality_reduction.ipynb
+++ b/_sources/Chapter2-DataManipulation/2.10_dimensionality_reduction.ipynb
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 1,
    "id": "881389fd-3239-4d3a-b073-ae0723a5624e",
    "metadata": {},
    "outputs": [],
@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 2,
    "id": "ba8e35ae",
    "metadata": {},
    "outputs": [],
@@ -184,17 +184,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 3,
    "id": "09ee7a7b",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
-     "execution_count": 42,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -227,7 +227,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 4,
    "id": "7fe2fc5e",
    "metadata": {},
    "outputs": [
@@ -312,13 +312,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "a89058bc",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
    "
       ]
@@ -359,14 +359,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 9,
    "id": "e5d1d348",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       ""
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "## Remove the mean of the data\n",
     "Xavg = np.mean(X, axis=1)                 # Compute mean\n",
-    "B = X - np.tile(Xavg,(nPoints,1)).T       # Mean-subtracted data"
+    "B = X - np.tile(Xavg,(nPoints,1)).T       # Mean-subtracted data\n",
+    "\n",
+    "plt.scatter(B[0,:],B[1,:], color='k', alpha=0.125)"
    ]
   },
   {
@@ -379,28 +402,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 10,
    "id": "0e2f63a6",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[[ 0.42469643  0.747179    0.85328813 ...  0.88246352 -1.884191\n",
-      "  -1.32403592]\n",
-      " [-0.18730514  0.80047482  1.11341706 ... -0.09048239 -2.95497644\n",
-      "  -0.18146037]]\n",
-      "[[ 0.42469643 -0.18730514]\n",
-      " [ 0.747179    0.80047482]\n",
-      " [ 0.85328813  1.11341706]\n",
-      " ...\n",
-      " [ 0.88246352 -0.09048239]\n",
-      " [-1.884191   -2.95497644]\n",
-      " [-1.32403592 -0.18146037]]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Find principal components (SVD): \n",
     "# use the option full_matrices =0 will calculate the covariance of B\n",
@@ -497,7 +502,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 11,
    "id": "3ff7e067-1e70-407a-9a65-463d84333559",
    "metadata": {},
    "outputs": [],
@@ -524,7 +529,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 12,
    "id": "c4af647d-efb8-460b-b92f-f164a8ad26ec",
    "metadata": {},
    "outputs": [
@@ -552,7 +557,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 13,
    "id": "81ddd943-7cdb-4fed-8ced-552b2bfa5b59",
    "metadata": {},
    "outputs": [
@@ -570,7 +575,7 @@
        "{'tags': ['hide-output']}"
       ]
      },
-     "execution_count": 91,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -590,7 +595,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 14,
    "id": "bb6d9182",
    "metadata": {},
    "outputs": [],
@@ -602,7 +607,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 15,
    "id": "916ebb13",
    "metadata": {},
    "outputs": [
@@ -643,17 +648,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 16,
    "id": "1e976d56",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
-     "execution_count": 98,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -717,7 +722,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 17,
    "id": "e00fa19e-43ef-4466-821b-40f3180b3768",
    "metadata": {},
    "outputs": [
@@ -737,7 +742,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 18,
    "id": "d54c0de2-d376-4c3f-bfb6-7776ad850388",
    "metadata": {},
    "outputs": [
@@ -758,7 +763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 19,
    "id": "5a84699a-cbf1-46a6-91ea-21a265f24512",
    "metadata": {},
    "outputs": [
@@ -785,7 +790,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 20,
    "id": "1785f2cb",
    "metadata": {},
    "outputs": [
@@ -806,7 +811,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 21,
    "id": "242e1397-c23d-4b84-9480-f375a3d3e8ad",
    "metadata": {},
    "outputs": [
@@ -823,7 +828,7 @@
        "Text(0.5, 1.0, 'Cumulative PCs')"
       ]
      },
-     "execution_count": 105,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -862,7 +867,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 22,
    "id": "e7c09351-6f23-4215-b5a5-6d1724e3884d",
    "metadata": {},
    "outputs": [
@@ -870,7 +875,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "minimum dimension size to explain 95% of the variance:  1\n"
+      "Minimum dimension size to explain 95% of the variance:  1\n"
      ]
     }
    ],
@@ -881,7 +886,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 23,
    "id": "fb2b0a52-c599-41ca-84d7-96b68823085f",
    "metadata": {},
    "outputs": [
@@ -911,7 +916,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 24,
    "id": "f5024fcd-922c-43a1-a673-84951f8cbe98",
    "metadata": {},
    "outputs": [
@@ -931,14 +936,6 @@
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[ 1.69  -0.668 -6.747]\n",
-      "[ 2.14194643 -1.44586065 -6.42108578]\n"
-     ]
     }
    ],
    "source": [
diff --git a/_sources/Chapter3-MachineLearning/3.3_binary_classification.ipynb b/_sources/Chapter3-MachineLearning/3.3_binary_classification.ipynb
index bc1433e..687de92 100644
--- a/_sources/Chapter3-MachineLearning/3.3_binary_classification.ipynb
+++ b/_sources/Chapter3-MachineLearning/3.3_binary_classification.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "6107cdf4",
    "metadata": {},
    "outputs": [],
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "id": "d396cc63",
    "metadata": {},
    "outputs": [],
@@ -72,13 +72,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "id": "be32d69c",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
    "
       ]
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "id": "85f7d5b3",
    "metadata": {},
    "outputs": [
@@ -136,20 +136,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "id": "da24f78d",
    "metadata": {},
    "outputs": [
     {
-     "ename": "ImportError",
-     "evalue": "cannot import name 'DecisionBoundaryDisplay' from 'sklearn.inspection' (/Users/marinedenolle/opt/miniconda3/envs/mlgeo_sk/lib/python3.9/site-packages/sklearn/inspection/__init__.py)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn [7], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39msklearn\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39minspection\u001b[39;00m \u001b[39mimport\u001b[39;00m DecisionBoundaryDisplay\n\u001b[1;32m      2\u001b[0m ax \u001b[39m=\u001b[39m plt\u001b[39m.\u001b[39msubplot()\n\u001b[1;32m      3\u001b[0m \u001b[39m# plot the decision boundary as a background\u001b[39;00m\n",
-      "\u001b[0;31mImportError\u001b[0m: cannot import name 'DecisionBoundaryDisplay' from 'sklearn.inspection' (/Users/marinedenolle/opt/miniconda3/envs/mlgeo_sk/lib/python3.9/site-packages/sklearn/inspection/__init__.py)"
-     ]
+     "data": {
+      "text/plain": [
+       ""
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -174,7 +183,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "76e3f16d",
    "metadata": {},
    "outputs": [
@@ -188,16 +197,16 @@
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
    "
       ]
@@ -207,7 +216,6 @@
     }
    ],
    "source": [
-    "\n",
     "# define ML\n",
     "K = 5\n",
     "clf= KNeighborsClassifier(K)\n",
@@ -223,60 +231,28 @@
     "\n",
     "# calculate the mean accuracy on the given test data and labels.\n",
     "score = clf.score(X_test, y_test)\n",
-    "print(\"The mean accuracy on the given test and labels is %f\" %score)\n",
-    "\n",
-    "# plot the decision boundary as a background\n",
-    "ax = plt.subplot()\n",
-    "# DecisionBoundaryDisplay.from_estimator(clf, X, cmap='PiYG', alpha=0.8, ax=ax, eps=0.5)\n",
-    "ax.scatter(X[:, 0], X[:, 1], c=y, cmap='PiYG', alpha=0.6, edgecolors=\"k\")\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c44c8f0d",
-   "metadata": {},
-   "source": [
-    "Now we will test the effect of **data normalization** before the classification. We will stretch the first axis of the data to see the effects."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "77348ef0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# make a data set\n",
-    "X, y = make_moons(noise=0.3, random_state=0)\n",
-    "X[:,0] = 10*X[:,0] "
+    "print(\"The mean accuracy on the given test and labels is %f\" %score)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "1152fc32",
+   "execution_count": 9,
+   "id": "df9ebb0c",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The mean accuracy on the given test and labels is 0.775000\n"
-     ]
-    },
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
-     "execution_count": 11,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
    "
       ]
@@ -286,64 +262,58 @@
     }
    ],
    "source": [
-    "\n",
-    "# define ML\n",
-    "K = 5\n",
-    "clf= KNeighborsClassifier(K)\n",
-    "\n",
-    "# normalize data.\n",
-    "# X = StandardScaler().fit_transform(X)\n",
-    "\n",
-    "# split data between train and test set.\n",
-    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42)\n",
-    "\n",
-    "# Fit the model.\n",
-    "clf.fit(X_train, y_train)\n",
-    "\n",
-    "# calculate the mean accuracy on the given test data and labels.\n",
-    "score = clf.score(X_test, y_test)\n",
-    "print(\"The mean accuracy on the given test and labels is %f\" %score)\n",
-    "\n",
     "# plot the decision boundary as a background\n",
     "ax = plt.subplot()\n",
-    "# DecisionBoundaryDisplay.from_estimator(clf, X, cmap='PiYG', alpha=0.8, ax=ax, eps=0.5)\n",
-    "ax.scatter(X[:, 0], X[:, 1], c=y, cmap='PiYG', alpha=0.6, edgecolors=\"k\")\n"
+    "DecisionBoundaryDisplay.from_estimator(clf, X, cmap='PiYG', alpha=0.8, ax=ax, eps=0.5)\n",
+    "ax.scatter(X[:, 0], X[:, 1], c=y, cmap='PiYG', alpha=0.6, edgecolors=\"k\")"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "e33a9bd5",
+   "id": "c44c8f0d",
    "metadata": {},
    "source": [
-    "This drastically reduces the performance."
+    "Now we will test to see what happens when you do not **normalize** your data before the classification. We will stretch the first axis of the data to see the effects."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "77348ef0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# make a data set\n",
+    "X, y = make_moons(noise=0.3, random_state=0)\n",
+    "X[:,0] = 10*X[:,0] "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "id": "3677e2dc",
+   "execution_count": 11,
+   "id": "1152fc32",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "The mean accuracy on the given test and labels is 0.975000\n"
+      "The mean accuracy on the given test and labels is 0.775000\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
-     "execution_count": 12,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
    "
       ]
@@ -358,9 +328,6 @@
     "K = 5\n",
     "clf= KNeighborsClassifier(K)\n",
     "\n",
-    "# normalize data.\n",
-    "X = StandardScaler().fit_transform(X)\n",
-    "\n",
     "# split data between train and test set.\n",
     "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42)\n",
     "\n",
@@ -377,6 +344,14 @@
     "ax.scatter(X[:, 0], X[:, 1], c=y, cmap='PiYG', alpha=0.6, edgecolors=\"k\")\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e33a9bd5",
+   "metadata": {},
+   "source": [
+    "This drastically reduces the performance."
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -385,7 +360,7 @@
    "source": [
     "## 2. Classifier Performance Metrics\n",
     "\n",
-    "In a binary classifier, we label one of the two classes as *positive*, the other class is negative. Let's consider *N* data samples.\n",
+    "In a binary classifier, we label one of the two classes as *positive*, the other class as *negative*. Let's consider *N* data samples.\n",
     "\n",
     "| True Class \\ predicted Class     | Positive            | Negative           | **Total** |\n",
     "|  -------------  |  -----------------  |  --------------- | ----- |\n",
@@ -412,10 +387,10 @@
     "\n",
     "**Other model performance metrics**\n",
     "Model peformance can be assessed with the following:\n",
-    "* **error** : the fraction of the data that was misclassified \n",
+    "* **Error** : the fraction of the data that was misclassified \n",
     "\n",
     "    $err = \\frac{FP+FN}{N}$  -> 0\n",
-    "* **accuracy**: the fraction of the data that was correctly classified: \n",
+    "* **Accuracy**: the fraction of the data that was correctly classified: \n",
     "    \n",
     "    $acc = \\frac{TP+TN}{N} = 1 - err $ --> 1\n",
     "\n",
@@ -447,7 +422,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "id": "6589a03a",
    "metadata": {},
    "outputs": [
@@ -489,7 +464,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "id": "05d701bf",
    "metadata": {},
    "outputs": [
@@ -592,7 +567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 16,
    "id": "21d83bb1",
    "metadata": {},
    "outputs": [],
@@ -640,7 +615,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 17,
    "id": "61e400ff",
    "metadata": {},
    "outputs": [
@@ -695,7 +670,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.8"
   },
   "vscode": {
    "interpreter": {
diff --git a/_sources/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb b/_sources/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb
index c8b0f6c..8beabf9 100644
--- a/_sources/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb
+++ b/_sources/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb
@@ -13,12 +13,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['data', 'target', 'frame', 'feature_names', 'target_names', 'images', 'DESCR'])"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import numpy as np\n",
     "from sklearn.datasets import load_digits,fetch_openml\n",
+    "from sklearn.metrics import ConfusionMatrixDisplay\n",
     "digits = load_digits()\n",
     "digits.keys()"
    ]
@@ -32,9 +44,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " \n"
+     ]
+    }
+   ],
    "source": [
     "# explore data type\n",
     "data,y = digits[\"data\"].copy(),digits[\"target\"].copy()\n",
@@ -52,9 +72,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0 1 2 3 4 5 6 7 8 9]\n",
+      "10\n"
+     ]
+    }
+   ],
    "source": [
     "Nclasses = len(np.unique(y))\n",
     "print(np.unique(y))\n",
@@ -71,9 +100,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAADSCAYAAAAi0d0oAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAAASFklEQVR4nO3db5CVZd0H8N8KsRsBsiLkkiUsOmPJIAHNJCbgsBCkBkmgLxhZxgYqGaM/M8sU5oJlkjZjhRnxBgNzlDLIJlMY2JymN7GyloYzSyw6GU6Kyx9F/no/L57HfaIld8Hr8rC7n88MM+x1zv29rwP82POd++w5ZUVRFAEAAJDYOaXeAAAA0D0pGwAAQBbKBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBtnoLa2NoYNG3ZGx9bX10dZWVnaDcFZyJxAx8wJdMycdG3dqmyUlZV16ldDQ0Opt3rW+dOf/hSf+tSnom/fvnHBBRfErbfeGq+//nqpt0UG5uTMPPnkk3HzzTfHyJEjo1evXmf8jY+uwZycvkOHDsV9990XU6dOjaqqqujfv398/OMfj/vvvz9OnDhR6u2RgTk5M3feeWd88pOfjMGDB0dFRUVccsklsXjx4njllVdKvbUsyoqiKEq9iVTWrVt30tc///nPY9OmTbF27dqT1qdMmRIf/OAHz/g8x44di7feeivKy8tP+9jjx4/H8ePHo6Ki4ozPn1pTU1NcccUV8dGPfjQWLFgQ//jHP+Kee+6Jq6++Oh5//PFSb4/EzMmZqa2tjYcffjjGjBkTL774YvTq1St2795d6m2RiTk5fc8++2yMGjUqJk+eHFOnTo0BAwbEE088Eb/+9a/jpptuigceeKDUWyQxc3JmZs2aFYMHD45LL700+vfvHzt27IjVq1fHkCFDoqmpKT7wgQ+UeotpFd3YLbfcUnTmIb7xxhvvwW7OXtOnTy+qqqqK/fv3t62tXr26iIjiiSeeKOHOeC+Yk8556aWXiqNHjxZFURTXXHNNcdFFF5V2Q7ynzEnHXnnlleLZZ59ttz5//vwiIorm5uYS7Ir3kjk5c7/85S+LiCgeeuihUm8luW71MqrOmDRpUowcOTIaGxtjwoQJ0bdv3/jmN78ZEREbN26Ma665JoYOHRrl5eUxYsSIuOOOO9pd/v3P1w7u3r07ysrK4p577omf/exnMWLEiCgvL49PfOIT8ec///mkY0/12sGysrJYtGhRbNiwIUaOHBnl5eVx2WWXxe9///t2+29oaIhx48ZFRUVFjBgxIlatWnXKzFdffTWef/75OHTo0Dv+eRw4cCA2bdoUc+fOjQEDBrSt33TTTdGvX7945JFH3vF4uidz0t7QoUPjfe97X4f3o+cwJyc7//zz47LLLmu3/rnPfS4iInbs2PGOx9M9mZPOefvx7du374yOP5v1LvUGSmHv3r0xffr0uPHGG2Pu3Lltl/bWrFkT/fr1i6997WvRr1+/2LJlS3z729+OAwcOxN13391h7i9+8Ys4ePBgLFy4MMrKyuL73/9+XH/99bFr164On6T88Y9/jEcffTS+/OUvR//+/eNHP/pRzJo1K1588cUYNGhQRERs3749pk2bFlVVVbFs2bI4ceJELF++PAYPHtwub+XKlbFs2bLYunVrTJo06b+e969//WscP348xo0bd9J6nz59YvTo0bF9+/YOHzfdkzmBjpmTjr388ssR8b9lhJ7JnLRXFEXs3bs3jh8/Hs3NzbFkyZLo1atX9/xeVOpLKzmd6nLexIkTi4gofvrTn7a7/6FDh9qtLVy4sOjbt29x+PDhtrV58+ad9BKKlpaWIiKKQYMGFa+99lrb+saNG4uIKB577LG2tdtvv73dniKi6NOnT7Fz5862tWeeeaaIiOLHP/5x29p1111X9O3bt3jppZfa1pqbm4vevXu3y3z7PFu3bm33mP7d+vXri4gonnrqqXa3zZ49u7jgggve8Xi6PnPS8Zz8Jy+j6nnMyenPSVEUxZEjR4qPfexjxfDhw4tjx46d9vF0Leak83OyZ8+eIiLafl144YXFww8/3Klju5oe9zKqiIjy8vKYP39+u/X3v//9bb8/ePBgvPrqq3HVVVfFoUOH4vnnn+8w94YbbojKysq2r6+66qqIiNi1a1eHx9bU1MSIESPavh41alQMGDCg7dgTJ07E5s2bY+bMmTF06NC2+1188cUxffr0dnn19fVRFEWHDfnNN9+MiDjlD11VVFS03U7PY06gY+bknS1atCj+9re/xcqVK6N37x75YgrCnJzKeeedF5s2bYrHHnssli9fHueff363fRfQHjn5H/rQh6JPnz7t1p977rlYunRpbNmyJQ4cOHDSbfv37+8w9yMf+chJX789AK2trad97NvHv33sv/71r3jzzTfj4osvbne/U6111tuDfuTIkXa3HT58+KT/COhZzAl0zJz8d3fffXesXr067rjjjvjMZz6TLJeux5y016dPn6ipqYmIiGuvvTYmT54cV155ZQwZMiSuvfbad51/NumRZeNUT6D37dsXEydOjAEDBsTy5ctjxIgRUVFREU8//XTU1dXFW2+91WFur169TrledOLdhd/Nse9GVVVVRETs2bOn3W179uw5qc3Ts5gT6Jg5ObU1a9ZEXV1dfPGLX4ylS5e+Z+fl7GROOjZ+/PioqqqKBx98UNnorhoaGmLv3r3x6KOPxoQJE9rWW1paSrir/zdkyJCoqKiInTt3trvtVGudNXLkyOjdu3ds27Yt5syZ07Z+9OjRaGpqOmkNeuqcwOno6XOycePG+MIXvhDXX3993Hfffe86j+6pp8/JqRw+fLhTV3S6mh75Mxun8nbD/fdGe/To0fjJT35Sqi2dpFevXlFTUxMbNmyIf/7zn23rO3fuPOUH73X2LdjOPffcqKmpiXXr1sXBgwfb1teuXRuvv/56zJ49O92DoMvrqXMCp6Mnz8lTTz0VN954Y0yYMCEefPDBOOccTzM4tZ46J2+88cYp7/OrX/0qWltb2707aHfgysb/GT9+fFRWVsa8efPi1ltvjbKysli7du1Z9fKM+vr6ePLJJ+PKK6+ML33pS3HixIlYuXJljBw5Mpqamk667+m8Bdt3v/vdGD9+fEycOLHtE8R/8IMfxNSpU2PatGn5HhBdTk+ek7/85S/xm9/8JiL+95vN/v374zvf+U5ERFx++eVx3XXX5Xg4dEE9dU5eeOGF+OxnPxtlZWXx+c9/PtavX3/S7aNGjYpRo0ZleDR0RT11Tpqbm6OmpiZuuOGGuPTSS+Occ86Jbdu2xbp162LYsGHxla98Je+DKgFl4/8MGjQofvvb38bXv/71WLp0aVRWVsbcuXNj8uTJ8elPf7rU24uIiLFjx8bjjz8e3/jGN+K2226LD3/4w7F8+fLYsWNHp9614b8ZM2ZMbN68Oerq6uKrX/1q9O/fP26++eb43ve+l3D3dAc9eU6efvrpuO22205ae/vrefPmKRu06alz0tLS0vYSkFtuuaXd7bfffruyQZueOicXXnhhzJo1K7Zs2RIPPPBAHDt2LC666KJYtGhRfOtb32r7jI/upKw4myokZ2TmzJnx3HPPRXNzc6m3AmctcwIdMyfQMXNyeryYsov5z8+9aG5ujt/97nc+JwD+jTmBjpkT6Jg5efdc2ehiqqqqora2Nqqrq+OFF16I+++/P44cORLbt2+PSy65pNTbg7OCOYGOmRPomDl59/zMRhczbdq0eOihh+Lll1+O8vLyuOKKK+LOO+/0Dx7+jTmBjpkT6Jg5efdc2QAAALLwMxsAAEAWygYAAJCFsgEAAGTR7X5A/D8/sTSFurq65JlTpkxJnhkRcddddyXPrKysTJ5J95PjbQD37duXPDMiYtmyZckzZ8yYkTyT7qehoSF55syZM5NnRkSMHj06eWaOx0/prVixInnmkiVLkmcOHz48eWZERGNjY/LM7vTcy5UNAAAgC2UDAADIQtkAAACyUDYAAIAslA0AACALZQMAAMhC2QAAALJQNgAAgCyUDQAAIAtlAwAAyELZAAAAslA2AACALJQNAAAgC2UDAADIQtkAAACyUDYAAIAslA0AACALZQMAAMhC2QAAALLoXeoNpFZXV5c8s6WlJXlma2tr8syIiPPOOy955iOPPJI8c/bs2ckzKa2BAwcmz/zDH/6QPDMiYuvWrckzZ8yYkTyT0mpqakqeefXVVyfPPPfcc5NnRkTs3r07Sy6ltWTJkuSZOZ4nrFq1KnnmwoULk2dGRDQ2NibPrKmpSZ5ZKq5sAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBsAAEAWygYAAJCFsgEAAGShbAAAAFkoGwAAQBbKBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBsAAEAWygYAAJCFsgEAAGTRu5Qnb2xsTJ7Z0tKSPPPvf/978szq6urkmRERU6ZMSZ6Z4+9p9uzZyTPpvKampuSZDQ0NyTNzGT16dKm3QBewYcOG5JmXX3558syZM2cmz4yIWLZsWZZcSmvBggXJM+vq6pJnjh07Nnnm8OHDk2dGRNTU1GTJ7S5c2QAAALJQNgAAgCyUDQAAIAtlAwAAyELZAAAAslA2AACALJQNAAAgC2UDAADIQtkAAACyUDYAAIAslA0AACALZQMAAMhC2QAAALJQNgAAgCyUDQAAIAtlAwAAyELZAAAAslA2AACALJQNAAAgC2UDAADIoncpT97a2po8c8yYMckzq6urk2fmMnbs2FJvgcTuvffe5Jn19fXJM/fv3588M5dJkyaVegt0AYsXL06eOWzYsOSZOfYZETFjxowsuZRWjuc0u3btSp7Z0tKSPLOmpiZ5ZkSe57OVlZXJM0vFlQ0AACALZQMAAMhC2QAAALJQNgAAgCyUDQAAIAtlAwAAyELZAAAAslA2AACALJQNAAAgC2UDAADIQtkAAACyUDYAAIAslA0AACALZQMAAMhC2QAAALJQNgAAgCyUDQAAIAtlAwAAyELZAAAAslA2AACALHqX8uStra3JM6dMmZI8syvJ8WdaWVmZPJPOW7x4cfLM2tra5Jld6d/Jvn37Sr0FEsvxd3rvvfcmz9ywYUPyzFzWrFlT6i3QRVRXVyfPfO2115Jn1tTUJM/Mlbt58+bkmaX6Pu3KBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBsAAEAWygYAAJCFsgEAAGShbAAAAFkoGwAAQBbKBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBsAAEAWygYAAJBF71KevLKyMnlmY2Nj8swcWltbs+Ru27YteeacOXOSZ0IpNTU1Jc8cPXp08kw6r76+PnnmD3/4w+SZOWzYsCFL7sCBA7PkQmfkeI64efPm5JkREQsXLkyeuWLFiuSZd911V/LMznBlAwAAyELZAAAAslA2AACALJQNAAAgC2UDAADIQtkAAACyUDYAAIAslA0AACALZQMAAMhC2QAAALJQNgAAgCyUDQAAIAtlAwAAyELZAAAAslA2AACALJQNAAAgC2UDAADIQtkAAACyUDYAAIAslA0AACCL3qU8eXV1dfLMbdu2Jc9cv359l8jMpa6urtRbAHhHtbW1yTMbGhqSZz7zzDPJM2fOnJk8MyJixowZyTPnz5+fPDPHPjk9S5YsSZ5ZU1OTPLO1tTV5ZkTEpk2bkmfOmTMneWapuLIBAABkoWwAAABZKBsAAEAWygYAAJCFsgEAAGShbAAAAFkoGwAAQBbKBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBsAAEAWygYAAJCFsgEAAGShbAAAAFkoGwAAQBbKBgAAkEXvUp68uro6eeaKFSuSZ9bV1SXPHDduXPLMiIjGxsYsuXQvAwcOTJ45Y8aM5JkbN25MnhkR0dDQkDyztrY2eSadN3r06OSZTU1NXSKzvr4+eWZEnvkbNmxY8swc//dweiorK5NnLliwIHlmLnPmzEmeuWrVquSZpeLKBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBsAAEAWygYAAJCFsgEAAGShbAAAAFkoGwAAQBbKBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABkoWwAAABZKBsAAEAWZUVRFKXeBAAA0P24sgEAAGShbAAAAFkoGwAAQBbKBgAAkIWyAQAAZKFsAAAAWSgbAABAFsoGAACQhbIBAABk8T8LB8QXOiCcUAAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# plot the data\n",
     "import matplotlib.pyplot as plt\n",
@@ -100,9 +140,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0 15.0\n",
+      "\n",
+      "[[0.     0.     0.3125 ... 0.     0.     0.    ]\n",
+      " [0.     0.     0.     ... 0.625  0.     0.    ]\n",
+      " [0.     0.     0.     ... 1.     0.5625 0.    ]\n",
+      " ...\n",
+      " [0.     0.     0.0625 ... 0.375  0.     0.    ]\n",
+      " [0.     0.     0.125  ... 0.75   0.     0.    ]\n",
+      " [0.     0.     0.625  ... 0.75   0.0625 0.    ]]\n"
+     ]
+    }
+   ],
    "source": [
     "print(min(data[0]),max(data[0]))\n",
     "from sklearn.preprocessing import MinMaxScaler\n",
@@ -122,9 +178,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 1797 data samples\n"
+     ]
+    }
+   ],
    "source": [
     "# Split data into 50% train and 50% test subsets\n",
     "from sklearn.model_selection import train_test_split\n",
@@ -135,9 +199,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SVC Accuracy: 0.9688542825361512\n",
+      "K-nearest Neighbors Accuracy: 0.9555061179087876\n",
+      "Random Forest Accuracy: 0.92880978865406\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    0.1s\n",
+      "[Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    0.0s\n"
+     ]
+    }
+   ],
    "source": [
     "import sklearn\n",
     "from sklearn import metrics\n",
@@ -166,9 +248,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "_, axes = plt.subplots(nrows=1, ncols=4, figsize=(10, 3))\n",
     "for ax, image, prediction in zip(axes, X_test, rf_prediction):\n",
@@ -180,52 +273,171 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Support Vector Machine\n",
+      "Classification report for classifier SVC(gamma=0.001):\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       1.00      0.99      0.99        88\n",
+      "           1       0.99      0.97      0.98        91\n",
+      "           2       0.99      0.99      0.99        86\n",
+      "           3       0.98      0.87      0.92        91\n",
+      "           4       0.99      0.96      0.97        92\n",
+      "           5       0.95      0.97      0.96        91\n",
+      "           6       0.99      0.99      0.99        91\n",
+      "           7       0.96      0.99      0.97        89\n",
+      "           8       0.94      1.00      0.97        88\n",
+      "           9       0.93      0.98      0.95        92\n",
+      "\n",
+      "    accuracy                           0.97       899\n",
+      "   macro avg       0.97      0.97      0.97       899\n",
+      "weighted avg       0.97      0.97      0.97       899\n",
+      "\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "print(\"Support Vector Machine\")\n",
     "print(f\"Classification report for classifier {clf}:\\n\"\n",
     "      f\"{metrics.classification_report(y_test, svc_prediction)}\\n\")\n",
-    "disp = metrics.plot_confusion_matrix(clf, X_test, y_test)\n",
+    "\n",
+    "disp = ConfusionMatrixDisplay.from_estimator(clf, X_test, y_test)\n",
     "disp.figure_.suptitle(\"Confusion Matrix\")\n",
-    "print(f\"Confusion matrix:\\n{disp.confusion_matrix}\")\n",
+    "# print(f\"Confusion matrix:\\n{disp.confusion_matrix}\")\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "K-nearest neighbors\n",
+      "Classification report for classifier KNeighborsClassifier():\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.99      1.00      0.99        88\n",
+      "           1       0.95      0.98      0.96        91\n",
+      "           2       0.98      0.93      0.95        86\n",
+      "           3       0.89      0.90      0.90        91\n",
+      "           4       1.00      0.95      0.97        92\n",
+      "           5       0.96      0.98      0.97        91\n",
+      "           6       0.99      1.00      0.99        91\n",
+      "           7       0.95      1.00      0.97        89\n",
+      "           8       0.95      0.90      0.92        88\n",
+      "           9       0.91      0.92      0.92        92\n",
+      "\n",
+      "    accuracy                           0.96       899\n",
+      "   macro avg       0.96      0.96      0.96       899\n",
+      "weighted avg       0.96      0.96      0.96       899\n",
+      "\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "print(\"K-nearest neighbors\")\n",
     "print(f\"Classification report for classifier {knn_clf}:\\n\"\n",
     "      f\"{metrics.classification_report(y_test, knn_prediction)}\\n\")\n",
-    "disp = metrics.plot_confusion_matrix(knn_clf, X_test, y_test)\n",
+    "disp = ConfusionMatrixDisplay.from_estimator(knn_clf, X_test, y_test)\n",
     "disp.figure_.suptitle(\"Confusion Matrix\")\n",
-    "print(f\"Confusion matrix:\\n{disp.confusion_matrix}\")\n",
+    "# print(f\"Confusion matrix:\\n{disp.confusion_matrix}\")\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Random Forest\n",
+      "Classification report for classifier RandomForestClassifier(random_state=42, verbose=True):\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.97      0.99      0.98        88\n",
+      "           1       0.95      0.89      0.92        91\n",
+      "           2       1.00      0.90      0.94        86\n",
+      "           3       0.87      0.84      0.85        91\n",
+      "           4       0.99      0.91      0.95        92\n",
+      "           5       0.91      0.96      0.93        91\n",
+      "           6       0.98      1.00      0.99        91\n",
+      "           7       0.93      0.98      0.95        89\n",
+      "           8       0.88      0.90      0.89        88\n",
+      "           9       0.84      0.93      0.89        92\n",
+      "\n",
+      "    accuracy                           0.93       899\n",
+      "   macro avg       0.93      0.93      0.93       899\n",
+      "weighted avg       0.93      0.93      0.93       899\n",
+      "\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    0.0s\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "print(\"Random Forest\")\n",
     "print(f\"Classification report for classifier {rf_clf}:\\n\"\n",
     "      f\"{metrics.classification_report(y_test, rf_prediction)}\\n\")\n",
-    "disp = metrics.plot_confusion_matrix(rf_clf, X_test, y_test)\n",
+    "disp = ConfusionMatrixDisplay.from_estimator(rf_clf, X_test, y_test)\n",
     "disp.figure_.suptitle(\"Confusion Matrix\")\n",
-    "print(f\"Confusion matrix:\\n{disp.confusion_matrix}\")\n",
+    "# print(f\"Confusion matrix:\\n{disp.confusion_matrix}\")\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -234,9 +446,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       ""
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "\n",
     "from sklearn.multiclass import OneVsRestClassifier\n",
@@ -282,12 +515,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "y should be a 1d array, got an array of shape (598, 10) instead.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[1;32m/workspaces/mlgeo-instructor/book/Chapter3-MachineLearning/3.4_multiclass_classification.ipynb Cell 20\u001b[0m line \u001b[0;36m2\n\u001b[1;32m      1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39msklearn\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mmodel_selection\u001b[39;00m \u001b[39mimport\u001b[39;00m cross_val_predict\n\u001b[0;32m----> 2\u001b[0m y_train_pred \u001b[39m=\u001b[39m cross_val_predict(clf,X_train,y_train,cv\u001b[39m=\u001b[39;49m\u001b[39m3\u001b[39;49m) \u001b[39m# predict using K-fold cross validation\u001b[39;00m\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/model_selection/_validation.py:1033\u001b[0m, in \u001b[0;36mcross_val_predict\u001b[0;34m(estimator, X, y, groups, cv, n_jobs, verbose, fit_params, pre_dispatch, method)\u001b[0m\n\u001b[1;32m   1030\u001b[0m \u001b[39m# We clone the estimator to make sure that all the folds are\u001b[39;00m\n\u001b[1;32m   1031\u001b[0m \u001b[39m# independent, and that it is pickle-able.\u001b[39;00m\n\u001b[1;32m   1032\u001b[0m parallel \u001b[39m=\u001b[39m Parallel(n_jobs\u001b[39m=\u001b[39mn_jobs, verbose\u001b[39m=\u001b[39mverbose, pre_dispatch\u001b[39m=\u001b[39mpre_dispatch)\n\u001b[0;32m-> 1033\u001b[0m predictions \u001b[39m=\u001b[39m parallel(\n\u001b[1;32m   1034\u001b[0m     delayed(_fit_and_predict)(\n\u001b[1;32m   1035\u001b[0m         clone(estimator), X, y, train, test, verbose, fit_params, method\n\u001b[1;32m   1036\u001b[0m     )\n\u001b[1;32m   1037\u001b[0m     \u001b[39mfor\u001b[39;49;00m train, test \u001b[39min\u001b[39;49;00m splits\n\u001b[1;32m   1038\u001b[0m )\n\u001b[1;32m   1040\u001b[0m inv_test_indices \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mempty(\u001b[39mlen\u001b[39m(test_indices), dtype\u001b[39m=\u001b[39m\u001b[39mint\u001b[39m)\n\u001b[1;32m   1041\u001b[0m inv_test_indices[test_indices] \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marange(\u001b[39mlen\u001b[39m(test_indices))\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/utils/parallel.py:65\u001b[0m, in \u001b[0;36mParallel.__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m     60\u001b[0m config \u001b[39m=\u001b[39m get_config()\n\u001b[1;32m     61\u001b[0m iterable_with_config \u001b[39m=\u001b[39m (\n\u001b[1;32m     62\u001b[0m     (_with_config(delayed_func, config), args, kwargs)\n\u001b[1;32m     63\u001b[0m     \u001b[39mfor\u001b[39;00m delayed_func, args, kwargs \u001b[39min\u001b[39;00m iterable\n\u001b[1;32m     64\u001b[0m )\n\u001b[0;32m---> 65\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49m\u001b[39m__call__\u001b[39;49m(iterable_with_config)\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/joblib/parallel.py:1863\u001b[0m, in \u001b[0;36mParallel.__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m   1861\u001b[0m     output \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_sequential_output(iterable)\n\u001b[1;32m   1862\u001b[0m     \u001b[39mnext\u001b[39m(output)\n\u001b[0;32m-> 1863\u001b[0m     \u001b[39mreturn\u001b[39;00m output \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mreturn_generator \u001b[39melse\u001b[39;00m \u001b[39mlist\u001b[39;49m(output)\n\u001b[1;32m   1865\u001b[0m \u001b[39m# Let's create an ID that uniquely identifies the current call. If the\u001b[39;00m\n\u001b[1;32m   1866\u001b[0m \u001b[39m# call is interrupted early and that the same instance is immediately\u001b[39;00m\n\u001b[1;32m   1867\u001b[0m \u001b[39m# re-used, this id will be used to prevent workers that were\u001b[39;00m\n\u001b[1;32m   1868\u001b[0m \u001b[39m# concurrently finalizing a task from the previous call to run the\u001b[39;00m\n\u001b[1;32m   1869\u001b[0m \u001b[39m# callback.\u001b[39;00m\n\u001b[1;32m   1870\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_lock:\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/joblib/parallel.py:1792\u001b[0m, in \u001b[0;36mParallel._get_sequential_output\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m   1790\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_dispatched_batches \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m   1791\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_dispatched_tasks \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[0;32m-> 1792\u001b[0m res \u001b[39m=\u001b[39m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1793\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_completed_tasks \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m   1794\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mprint_progress()\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/utils/parallel.py:127\u001b[0m, in \u001b[0;36m_FuncWrapper.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    125\u001b[0m     config \u001b[39m=\u001b[39m {}\n\u001b[1;32m    126\u001b[0m \u001b[39mwith\u001b[39;00m config_context(\u001b[39m*\u001b[39m\u001b[39m*\u001b[39mconfig):\n\u001b[0;32m--> 127\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfunction(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/model_selection/_validation.py:1115\u001b[0m, in \u001b[0;36m_fit_and_predict\u001b[0;34m(estimator, X, y, train, test, verbose, fit_params, method)\u001b[0m\n\u001b[1;32m   1113\u001b[0m     estimator\u001b[39m.\u001b[39mfit(X_train, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mfit_params)\n\u001b[1;32m   1114\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m-> 1115\u001b[0m     estimator\u001b[39m.\u001b[39;49mfit(X_train, y_train, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mfit_params)\n\u001b[1;32m   1116\u001b[0m func \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39m(estimator, method)\n\u001b[1;32m   1117\u001b[0m predictions \u001b[39m=\u001b[39m func(X_test)\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/base.py:1152\u001b[0m, in \u001b[0;36m_fit_context..decorator..wrapper\u001b[0;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1145\u001b[0m     estimator\u001b[39m.\u001b[39m_validate_params()\n\u001b[1;32m   1147\u001b[0m \u001b[39mwith\u001b[39;00m config_context(\n\u001b[1;32m   1148\u001b[0m     skip_parameter_validation\u001b[39m=\u001b[39m(\n\u001b[1;32m   1149\u001b[0m         prefer_skip_nested_validation \u001b[39mor\u001b[39;00m global_skip_validation\n\u001b[1;32m   1150\u001b[0m     )\n\u001b[1;32m   1151\u001b[0m ):\n\u001b[0;32m-> 1152\u001b[0m     \u001b[39mreturn\u001b[39;00m fit_method(estimator, \u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/svm/_base.py:190\u001b[0m, in \u001b[0;36mBaseLibSVM.fit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    188\u001b[0m     check_consistent_length(X, y)\n\u001b[1;32m    189\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 190\u001b[0m     X, y \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_validate_data(\n\u001b[1;32m    191\u001b[0m         X,\n\u001b[1;32m    192\u001b[0m         y,\n\u001b[1;32m    193\u001b[0m         dtype\u001b[39m=\u001b[39;49mnp\u001b[39m.\u001b[39;49mfloat64,\n\u001b[1;32m    194\u001b[0m         order\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mC\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m    195\u001b[0m         accept_sparse\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mcsr\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m    196\u001b[0m         accept_large_sparse\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m,\n\u001b[1;32m    197\u001b[0m     )\n\u001b[1;32m    199\u001b[0m y \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_validate_targets(y)\n\u001b[1;32m    201\u001b[0m sample_weight \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39masarray(\n\u001b[1;32m    202\u001b[0m     [] \u001b[39mif\u001b[39;00m sample_weight \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m sample_weight, dtype\u001b[39m=\u001b[39mnp\u001b[39m.\u001b[39mfloat64\n\u001b[1;32m    203\u001b[0m )\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/base.py:622\u001b[0m, in \u001b[0;36mBaseEstimator._validate_data\u001b[0;34m(self, X, y, reset, validate_separately, cast_to_ndarray, **check_params)\u001b[0m\n\u001b[1;32m    620\u001b[0m         y \u001b[39m=\u001b[39m check_array(y, input_name\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39my\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mcheck_y_params)\n\u001b[1;32m    621\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 622\u001b[0m         X, y \u001b[39m=\u001b[39m check_X_y(X, y, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mcheck_params)\n\u001b[1;32m    623\u001b[0m     out \u001b[39m=\u001b[39m X, y\n\u001b[1;32m    625\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m no_val_X \u001b[39mand\u001b[39;00m check_params\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39mensure_2d\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mTrue\u001b[39;00m):\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/utils/validation.py:1162\u001b[0m, in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001b[0m\n\u001b[1;32m   1142\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[1;32m   1143\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mestimator_name\u001b[39m}\u001b[39;00m\u001b[39m requires y to be passed, but the target y is None\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m   1144\u001b[0m     )\n\u001b[1;32m   1146\u001b[0m X \u001b[39m=\u001b[39m check_array(\n\u001b[1;32m   1147\u001b[0m     X,\n\u001b[1;32m   1148\u001b[0m     accept_sparse\u001b[39m=\u001b[39maccept_sparse,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1159\u001b[0m     input_name\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mX\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m   1160\u001b[0m )\n\u001b[0;32m-> 1162\u001b[0m y \u001b[39m=\u001b[39m _check_y(y, multi_output\u001b[39m=\u001b[39;49mmulti_output, y_numeric\u001b[39m=\u001b[39;49my_numeric, estimator\u001b[39m=\u001b[39;49mestimator)\n\u001b[1;32m   1164\u001b[0m check_consistent_length(X, y)\n\u001b[1;32m   1166\u001b[0m \u001b[39mreturn\u001b[39;00m X, y\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/utils/validation.py:1183\u001b[0m, in \u001b[0;36m_check_y\u001b[0;34m(y, multi_output, y_numeric, estimator)\u001b[0m\n\u001b[1;32m   1181\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   1182\u001b[0m     estimator_name \u001b[39m=\u001b[39m _check_estimator_name(estimator)\n\u001b[0;32m-> 1183\u001b[0m     y \u001b[39m=\u001b[39m column_or_1d(y, warn\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\n\u001b[1;32m   1184\u001b[0m     _assert_all_finite(y, input_name\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39my\u001b[39m\u001b[39m\"\u001b[39m, estimator_name\u001b[39m=\u001b[39mestimator_name)\n\u001b[1;32m   1185\u001b[0m     _ensure_no_complex_data(y)\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/sklearn/utils/validation.py:1244\u001b[0m, in \u001b[0;36mcolumn_or_1d\u001b[0;34m(y, dtype, warn)\u001b[0m\n\u001b[1;32m   1233\u001b[0m         warnings\u001b[39m.\u001b[39mwarn(\n\u001b[1;32m   1234\u001b[0m             (\n\u001b[1;32m   1235\u001b[0m                 \u001b[39m\"\u001b[39m\u001b[39mA column-vector y was passed when a 1d array was\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1240\u001b[0m             stacklevel\u001b[39m=\u001b[39m\u001b[39m2\u001b[39m,\n\u001b[1;32m   1241\u001b[0m         )\n\u001b[1;32m   1242\u001b[0m     \u001b[39mreturn\u001b[39;00m _asarray_with_order(xp\u001b[39m.\u001b[39mreshape(y, (\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m,)), order\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mC\u001b[39m\u001b[39m\"\u001b[39m, xp\u001b[39m=\u001b[39mxp)\n\u001b[0;32m-> 1244\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[1;32m   1245\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39my should be a 1d array, got an array of shape \u001b[39m\u001b[39m{}\u001b[39;00m\u001b[39m instead.\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(shape)\n\u001b[1;32m   1246\u001b[0m )\n",
+      "\u001b[0;31mValueError\u001b[0m: y should be a 1d array, got an array of shape (598, 10) instead."
+     ]
+    }
+   ],
    "source": [
     "from sklearn.model_selection import cross_val_predict\n",
-    "y_train_pred = cross_val_predict(clf,X_train,y_train,cv=3) # predict using K-fold cross validation"
+    "y_train_pred = cross_val_predict(clf, X_train, y_train, cv=3) # predict using K-fold cross validation"
    ]
   }
  ],
@@ -298,8 +555,16 @@
    "name": "python3"
   },
   "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
    "name": "python",
-   "version": "3.9.6"
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.8"
   },
   "orig_nbformat": 4,
   "vscode": {
diff --git a/reports/3.4_multiclass_classification.log b/reports/3.4_multiclass_classification.log
index 99ff672..97a1874 100644
--- a/reports/3.4_multiclass_classification.log
+++ b/reports/3.4_multiclass_classification.log
@@ -19,6 +19,7 @@ nbclient.exceptions.CellExecutionError: An error occurred while executing the fo
 ------------------
 import numpy as np
 from sklearn.datasets import load_digits,fetch_openml
+from sklearn.metrics import ConfusionMatrixDisplay
 digits = load_digits()
 digits.keys()
 ------------------
@@ -28,7 +29,7 @@ digits.keys()
 Input In [1], in ()
 ----> 1 import numpy as np
       2 from sklearn.datasets import load_digits,fetch_openml
-      3 digits = load_digits()
+      3 from sklearn.metrics import ConfusionMatrixDisplay
 
 ModuleNotFoundError: No module named 'numpy'
 ModuleNotFoundError: No module named 'numpy'
diff --git a/searchindex.js b/searchindex.js
index f7a9063..b9f8561 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
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Open Reproducible Science","1.3 Jupyter Environment","1.3 Python Ecosystem","1.4 Computing Environments","1.5 Version Control & GitHub","Getting Started","2.10 Dimensionality Reduction","2.10 ML-ready data","2.1 Data Definitions","2.2 Data Formats","2.4 Pandas","2.3 Data Arrays","2.6 Resampling Methods","2.7 Spectral Transforms","2.8 Statistical Considerations for geoscientific Data and Noise","2.9 Feature engineering","3.1 Clustering","3.2 Classification and Regression","3.3 Binary classification","3.4 Multiclass Classification","3.5 Logistic regression","3.6 Random Forests","3.7 Hyperparameter Tuning","3.8 Ensemble learning","3.9 AutoML","4.1 Neural Networks","4.2 Multi Layer Perceptrons","4.3 Convolutional Neural Networks","4.4  Recurrent Neural Networks: Processing sequences","4.5 Auto-encoders","4.6 NAS: Network Architecture Search","This chapter focuces on model workflow and ML reproducibility","The MLGeo Project","Machine Learning in the Geosciences","Acknowledgements from 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\ No newline at end of file

    • True Class \ predicted Class