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12. Choosing the right estimator — scikit-learn...
Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estimators are better suited for different types of data and different problem...scikit-learn.org/stable/machine_learning_map.html -
has_fit_parameter — scikit-learn 1.6.1 document...
Skip to main content Back to top Ctrl + K GitHub Choose version has_fit_parameter # sklearn.utils.validation. has_fit...scikit-learn.org/stable/modules/generated/sklearn.utils.validation.has_fit_parameter.html -
estimator_html_repr — scikit-learn 1.6.1 docume...
Skip to main content Back to top Ctrl + K GitHub Choose version estimator_html_repr # sklearn.utils. estimator_html_r...scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_html_repr.html -
Principal Component Analysis (PCA) on Iris Data...
figure ( 1 , figsize = ( 8 , 6 )) ax = fig...X_reduced [:, 0 ], X_reduced [:, 1 ], X_reduced [:, 2 ], c = iris...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_iris.html -
Support — scikit-learn 1.6.1 documentation
# This documentation is for 1.6.1. Find documentation for other...scikit-learn.org/stable/support.html -
GenericUnivariateSelect — scikit-learn 1.6.1 do...
Added in version 1.0. See also f_classif ANOVA F-value..."x1", ..., "x(n_features_in_ - 1)"] . If input_features is an array-like,...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.GenericUnivariateSelect.html -
One-class SVM with non-linear kernel (RBF) — sc...
reshape ( - 1 , 1 ), yy . reshape ( - 1 , 1 )], axis = 1 ) DecisionBoundaryDisp...OneClassSVM ( nu = 0.1 , kernel = "rbf" , gamma = 0.1 ) clf . fit (...scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html -
density — scikit-learn 1.6.1 documentation
between 0 and 1. Examples >>> from scipy import...scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.density.html -
MethodMapping — scikit-learn 1.6.1 documentation
Added in version 1.3. add ( * , caller , callee )...scikit-learn.org/stable/modules/generated/sklearn.utils.metadata_routing.MethodMapping.html -
MinCovDet — scikit-learn 1.6.1 documentation
algorithm: (n_samples + n_features + 1) / 2 * n_samples . The parameter...parameter must be in the range (0, 1]. random_state int, RandomState...scikit-learn.org/stable/modules/generated/sklearn.covariance.MinCovDet.html