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plot_classifier_comparison.ipynb
x_min, x_max = X[:, 0].min() - 0.5, X[:, 0].max() + 0.5\n y_min,...GaussianProcessClass(1.0 * RBF(1.0), random_state=42),\n DecisionTreeClassifi(max_depth=5,...scikit-learn.org/stable/_downloads/3438aba177365cb595921cf18806dfa7/plot_classifier_comparison.ipynb -
StackingClassifier — scikit-learn 1.7.1 documen...
RandomForestClassifi ( n_estimators = 10 , random_state = 42 )), ... ( 'svr' ,...load_iris ( return_X_y = True ) >>> estimators = [ ... ( 'rf' , RandomForestClassifi...scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingClassifier.html -
StackingRegressor — scikit-learn 1.7.1 document...
RidgeCV ()), ... ( 'svr' , LinearSVR ( random_state = 42 )) ... ] >>>...X_test , y_test ) 0.3... fit ( X , y , ** fit_params ) [source] #...scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingRegressor.html -
mutual_info_regression — scikit-learn 1.7.1 doc...
42 ... ) >>> mutual_info_regression ( X , y ) array([0.117, 2.645,...Sets”. PLoS ONE 9(2), 2014. [ 4 ] L. F. Kozachenko, N. N. Leonenko,...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.mutual_info_regression.html -
mutual_info_classif — scikit-learn 1.7.1 docume...
y ) array([0.589, 0.107, 0.196, 0.0968 , 0., 0. , 0. , 0. , 0....Sets”. PLoS ONE 9(2), 2014. [ 4 ] L. F. Kozachenko, N. N. Leonenko,...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.mutual_info_classif.html -
LinearSVC — scikit-learn 1.7.1 documentation
= 'auto' , tol = 0.0001 , C = 1.0 , multi_class = 'ovr' , fit_intercept...becomes [x_1, ..., x_n, intercept_scaling] , i.e. a “synthetic” feature...scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html -
get_scorer — scikit-learn 1.7.1 documentation
, - 1 , - 0.5 , 2 ], ( - 1 , 1 )) >>> y = np . array ([ 0 , 1...get_scorer ( "accuracy" ) >>> accuracy ( classifier , X , y ) 0.4 Gallery...scikit-learn.org/stable/modules/generated/sklearn.metrics.get_scorer.html -
RegressorMixin — scikit-learn 1.7.1 documentation
estimator . fit ( X , y ) . predict ( X ) array([0, 0, 0]) >>> estimator...of squares ((y_true - y_true.mean()) ** 2).sum() . The best possible...scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html -
make_column_transformer — scikit-learn 1.7.1 do...
er ( ... ( StandardScaler (), [ 'numerical_column' ]), ... (...['numerical_column']), ('onehotencoder', OneHotEncoder(...), ['categorical_column'])])...scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_transformer.html -
EmpiricalCovariance — scikit-learn 1.7.1 docume...
covariance_ array([[0.7569, 0.2818], [0.2818, 0.3928]]) >>> cov . location_...sqrt(tr(A^t.A)) - ‘spectral’: sqrt(max(eigenvalues(A^t.A)) where...scikit-learn.org/stable/modules/generated/sklearn.covariance.EmpiricalCovariance.html