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Precision-Recall — scikit-learn 1.5.2 documenta...
positives ( \(F_p\) ). \[P = \frac{T_p}{T_p+F_p}\] Recall ( \(R\)...negatives ( \(F_n\) ). \[R = \frac{T_p}{T_p + F_n}\] The precision-recall...scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html -
LeavePGroupsOut — scikit-learn 1.5.2 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 -
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 -
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.... -
Illustration of prior and posterior Gaussian pr...
label = f "Sampled function # { idx + 1...plt . tight_layout () print ( f "Kernel parameters before fit:...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_prior_posterior.html -
Hierarchical clustering: structured vs unstruct...
print ( f "Elapsed time: { elapsed_time : .2f } s" ) print ( f "Number...print ( f "Elapsed time: { elapsed_time : .2f } s" ) print ( f "Number...scikit-learn.org/stable/auto_examples/cluster/plot_ward_structured_vs_unstructured.html -
Gaussian Processes regression: basic introducto...
generative process is defined as \(f(x) = x \sin(x)\) . import numpy.... plot ( X , y , label = r "$f(x) = x \sin(x)$" , linestyle =...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_noisy_targets.html -
SelectFdr — scikit-learn 1.5.2 documentation
See also f_classif ANOVA F-value between label/feature...for classification tasks. f_regression F-value between label/feature...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFdr.html -
SelectFwe — scikit-learn 1.5.2 documentation
See also f_classif ANOVA F-value between label/feature...for classification tasks. f_regression F-value between label/feature...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFwe.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