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label_ranking_loss — scikit-learn 1.7.2 documen...
[[ 1 , 0 , 0 ], [ 0 , 0 , 1 ]] >>> y_score = [[ 0.75 , 0.5 ,..., 1 ], [ 1 , 0.2 , 0.1 ]] >>> label_ranking_loss ( y_true , y_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.label_ranking_loss.html -
Precision-Recall — scikit-learn 1.7.2 documenta...
Parameters steps [('standardscaler', ...), ('linearsvc', ...)] transform_input...Pipeline(steps=[('standardscaler', StandardScaler()), ('linearsvc', Linear...scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html -
SVM-Anova: SVM with univariate feature selectio...
SelectPercentile ( f_classif )), ( "scaler" , StandardScaler ()), ( "svc"...selected" ) plt . xticks ( np . linspace ( 0 , 100 , 11 , endpoint...scikit-learn.org/stable/auto_examples/svm/plot_svm_anova.html -
supervised_learning.rst.txt
.. _supervised-learning: Supervised learning ---------- .. toctree::...modules/kernel_ridge.rst modules/svm modules/sgd modules/neighbors modules/gaussian_process...scikit-learn.org/stable/_sources/supervised_learning.rst.txt -
spectral_embedding — scikit-learn 1.7.2 documen...
int ( X . shape [ 0 ] / 10 ), include_self = True ... ) >>> #...subspace. eigen_solver {‘arpack’, ‘lobpcg’, ‘amg’}, default=None...scikit-learn.org/stable/modules/generated/sklearn.manifold.spectral_embedding.html -
PairwiseKernel — scikit-learn 1.7.2 documentation
array([[0.8880, 0.05663, 0.05532], [0.8676, 0.07073, 0.06165]]) __call__...tuning. metric {“linear”, “additive_chi2”, “chi2”, “poly”, “polynomial”,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.PairwiseKernel.html -
SkewedChi2Sampler — scikit-learn 1.7.2 document...
1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...SkewedChi2Sampler ( skewedness = .01 , ... n_components = 10 , ... random_state...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.SkewedChi2Sampler.html -
SelectFwe — scikit-learn 1.7.2 documentation
generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features...SelectFwe ( chi2 , alpha = 0.01 ) . fit_transform ( X , y ) >>> X_new...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFwe.html -
IsolationForest example — scikit-learn 1.7.2 do...
= np . array ([[ 0.5 , - 0.1 ], [ 0.7 , 0.4 ]]) cluster_1 = 0.4..."predict" , alpha = 0.5 , ) disp . ax_ . scatter ( X [:, 0 ], X [:, 1...scikit-learn.org/stable/auto_examples/ensemble/plot_isolation_forest.html -
Multi-class AdaBoosted Decision Trees — scikit-...
algorithm" ) plt . plot ( [ boosting_errors . index . min (), boosting_errors...X_test ) ], } ) . set_index ( "Number of trees" ) ax = boosting_errors...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_multiclass.html