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LeavePGroupsOut — scikit-learn 1.7.2 documentation
print ( f "Fold { i } :" ) ... print ( f " Train: index=...train_index ] } " ) ... print ( f " Test: index= { test_index }...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePGroupsOut.html -
The Johnson-Lindenstrauss bound for embedding w...
legend ([ f "eps = { eps : 0.1f } " for eps...color = color ) plt . legend ([ f "n_samples = { n } " for n in...scikit-learn.org/stable/auto_examples/miscellaneous/plot_johnson_lindenstrauss_bound.html -
Feature agglomeration vs. univariate selection ...
BayesianRidge f_regression = mem . cache ( feature_selection . f_regression...univariate_selection.f_regression... f_regression(array([[-0.451933,...scikit-learn.org/stable/auto_examples/cluster/plot_feature_agglomeration_vs_univariate_selection.... -
1.13. Feature selection — scikit-learn 1.7.2 do...
f_classif , mutual_info_classif The methods based on F-test...estimator. For instance, we can use a F-test to retrieve the two best...scikit-learn.org/stable/modules/feature_selection.html -
2.2. Manifold learning — scikit-learn 1.7.2 doc...
scikit-learn.org/stable/modules/manifold.html -
Scalable learning with polynomial kernel approx...
annotate ( f "n_comp.= { n_components } " , ( results [ f "LSVM +..."score" : lsvm_score } print ( f "Linear SVM score on raw features:...scikit-learn.org/stable/auto_examples/kernel_approximation/plot_scalable_poly_kernels.html -
Multiclass Receiver Operating Characteristic (R...
name = f " { class_of_interest } vs the...effect of numpy.ravel : print ( f "y_score: \n { y_score [ 0 : 2...scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html -
L1 Penalty and Sparsity in Logistic Regression ...
* 100 print ( f "C= { C : .2f } " ) print ( f " { 'Sparsity with...sparsity_l1_LR : .2f } %" ) print ( f " { 'Sparsity with Elastic-Net...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_l1_l2_sparsity.html -
Combine predictors using stacking — scikit-lear...
{ key : ( f " { np . abs ( np . mean ( scores [ f 'test_ { value...])) : .2f } +- " f " { np . std ( scores [ f 'test_ { value }...scikit-learn.org/stable/auto_examples/ensemble/plot_stack_predictors.html -
7.1. Pipelines and composite estimators — sciki...
'w' ) as f : ... f . write ( estimator_html_repr...TransformedTargetReg(...) >>> print ( f "R2 score: { regr . score ( X_test...scikit-learn.org/stable/modules/compose.html