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scale — scikit-learn 1.7.2 documentation
import scale >>> X = [[ - 2 , 1 , 2 ], [ - 1 , 0 , 1 ]] >>> scale...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html -
OneClassSVM — scikit-learn 1.7.2 documentation
scikit-learn.org/stable/modules/generated/sklearn.svm.OneClassSVM.html -
SelectorMixin — scikit-learn 1.7.2 documentation
mask [: 2 ] = True # select the first two...fit_transform ( X , y ) . shape (150, 2) fit_transform ( X , y = None...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectorMixin.html -
Map data to a normal distribution — scikit-lear...
figaspect ( 2 )) axes = axes . flatten () axes_idxs..., 9 ), ( 1 , 4 , 7 , 10 ), ( 2 , 5 , 8 , 11 ), ( 12 , 15 , 18...scikit-learn.org/stable/auto_examples/preprocessing/plot_map_data_to_normal.html -
9.1. Strategies to scale computationally: bigge...
scikit-learn.org/stable/computing/scaling_strategies.html -
MultiLabelBinarizer — scikit-learn 1.7.2 docume...
2 ), ( 3 ,)]) array([[1, 1, 0],...>>> mlb . classes_ array([1, 2, 3]) >>> mlb . fit_transform ([{...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MultiLabelBinarizer.html -
CategoricalNB — scikit-learn 1.7.2 documentation
2. Changed in version 1.4: The default...)) >>> y = np . array ([ 1 , 2 , 3 , 4 , 5 , 6 ]) >>> from sklearn.naive_bayes...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.CategoricalNB.html -
3.3. Tuning the decision threshold for class pr...
DecisionTreeClassifi ( max_depth = 2 , random_state = 0 ) . fit ( X...best_score_ np.float64(0.86) 3.3.1.2. Important notes regarding the...scikit-learn.org/stable/modules/classification_threshold.html -
Density Estimation for a Gaussian mixture — sci...
2 ) + np . array ([ 20 , 20 ]) #...random . randn ( n_samples , 2 ), C ) # concatenate the two datasets...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_pdf.html -
Binarizer — scikit-learn 1.7.2 documentation
2. ], ... [ 2. , 0. , 0. ], ... [ 0. ,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Binarizer.html