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BaggingClassifier — scikit-learn 1.7.2 document...
max_samples = 1.0 , max_features = 1.0 , bootstrap = True...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html -
LeavePOut — scikit-learn 1.7.2 documentation
3] Test: index=[0 1] Fold 1: Train: index=[1 3] Test: index=[0...index=[1 2] Fold 4: Train: index=[0 2] Test: index=[1 3] Fold...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePOut.html -
Feature agglomeration vs. univariate selection ...
0 ][ 1 ] . inverse_transform ( coef_ . reshape ( 1 , - 1 )) coef_selection_...roi_size ] = - 1.0 coef [ - roi_size :, - roi_size :] = 1.0 X = np...scikit-learn.org/stable/auto_examples/cluster/plot_feature_agglomeration_vs_univariate_selection.... -
RidgeClassifierCV — scikit-learn 1.7.2 document...
1, 1.0, 10.0) , * , fit_intercept...shape (n_alphas,), default=(0.1, 1.0, 10.0) Array of alpha values...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifierCV.html -
Restricted Boltzmann Machine features for digit...
1 )) # 0-1 scaling X_train , X_test...False tol 1 C 100.0 fit_intercept True intercept_scaling 1 class_weight...scikit-learn.org/stable/auto_examples/neural_networks/plot_rbm_logistic_classification.html -
Adjustment for chance in clustering performance...
mean ( axis = 1 ), scores . std ( axis = 1 ), alpha = 0.8 ,...scores , axis = 1 ), scores . std ( axis = 1 ), alpha = 0.8 ,...scikit-learn.org/stable/auto_examples/cluster/plot_adjusted_for_chance_measures.html -
Ledoit-Wolf vs OAS estimation — scikit-learn 1....
covariance matrix (AR(1) process) r = 0.1 real_cov = toeplitz (...plot MSE plt . subplot ( 2 , 1 , 1 ) plt . errorbar ( n_samples_range...scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html -
all_estimators — scikit-learn 1.7.2 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version all_estimators # sklearn.utils.discovery. all_estimat...scikit-learn.org/stable/modules/generated/sklearn.utils.discovery.all_estimators.html -
sklearn.multioutput — scikit-learn 1.7.2 docume...
Multioutput regression and classification. The estimators provided in this module are meta-estimators: they require a base estimator to be provided in their constructor. The meta-estimator extends ...scikit-learn.org/stable/api/sklearn.multioutput.html -
sklearn.covariance — scikit-learn 1.7.2 documen...
Methods and algorithms to robustly estimate covariance. They estimate the covariance of features at given sets of points, as well as the precision matrix defined as the inverse of the covariance. C...scikit-learn.org/stable/api/sklearn.covariance.html