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Support Vector Machines — scikit-learn 1.7.2 do...
sklearn.svm module. One-class SVM with non-linear kernel (RBF) One-class...One-class SVM with non-linear kernel (RBF) Plot classification...scikit-learn.org/stable/auto_examples/svm/index.html -
Release Highlights — scikit-learn 1.7.2 documen...
scikit-learn 1.1 Release Highlights for scikit-learn 1.0 Release...scikit-learn 1.2 Release Highlights for scikit-learn 1.1 Release...scikit-learn.org/stable/auto_examples/release_highlights/index.html -
Release Highlights for scikit-learn 1.0 — sciki...
, 0.5 , 0.5 , 0. ], [0. , 0.125, 0.75 , 0.125], [0. , 0. , 0.5...array([[0.5 , 0.5 , 0. , 0. ], [0.125, 0.75 , 0.125, 0. ], [0....scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html -
permutation_importance — scikit-learn 1.7.2 doc...
9 , 9 ],[ 1 , 9 , 9 ],[ 1 , 9 , 9 ], ... [ 0 , 9 , 9 ],[ 0 , 9...9 , 9 ],[ 0 , 9 , 9 ]] >>> y = [ 1 , 1 , 1 , 0 , 0 , 0 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.inspection.permutation_importance.html -
StackingClassifier — scikit-learn 1.7.2 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 -
Cross decomposition — scikit-learn 1.7.2 docume...
top Ctrl + K GitHub Choose version Cross decomposition # Examples...concerning the sklearn.cross_decomposition module. Compare cross decomposition...scikit-learn.org/stable/auto_examples/cross_decomposition/index.html -
Pipeline — scikit-learn 1.7.2 documentation
'scaler' , StandardScaler ()), ( 'svc' , SVC ())]) >>> # The...train_test_split ( X , y , ... random_state = 0 ) >>> pipe = Pipeline ([( 'scaler'...scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html -
OrthogonalMatchingPursuitCV — scikit-learn 1.7....
1 ,]) array([-78.3854]) fit ( X , y , ** fit_params ) [source]...= 5 ) . fit ( X , y ) >>> reg . score ( X , y ) 0.9991 >>> reg...scikit-learn.org/stable/modules/generated/sklearn.linear_model.OrthogonalMatchingPursuitCV.html -
make_sparse_coded_signal — scikit-learn 1.7.2 d...
= 50 , ... n_components = 100 , ... n_features = 10 , ... n_nonzero_coefs...= 4 , ... random_state = 0 ... ) >>> data . shape (50, 10) >>>...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_coded_signal.html -
make_regression — scikit-learn 1.7.2 documentation
[-0.2341, -0.2341], [-0.4694, 0.5425], [ 1.579, 0.7674]]) >>> y...42 ) >>> X array([[ 0.4967, -0.1382 ], [ 0.6476, 1.523], [-0.2341,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html