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Support — scikit-learn 1.7.0 documentation
Resources # This documentation is for 1.7.0. Documentation for other versions...scikit-learn.org/stable/support.html -
Label Propagation digits: Demonstrating perform...
support 0 1.00 1.00 1.00 27 1 0.82 1.00 0.90 37 2 1.00 0.86 0.92...0.92 28 3 1.00 0.80 0.89 35 4 0.92 1.00 0.96 24 5 0.74 0.94 0.83...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits.html -
Biclustering documents with the Spectral Co-clu...
Done in 1.18s. V-measure: 0.4415 MiniBatchKMeans......alphalpha, proline, benson bicluster 1 : 1948 documents, 4325 words categories...scikit-learn.org/stable/auto_examples/bicluster/plot_bicluster_newsgroups.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 -
Multi-class AdaBoosted Decision Trees — scikit-...
as depicted by Figure 1 in Zhu et al [ 1 ] . The core principle...of trees" : range ( 1 , n_estimators + 1 ), "AdaBoost" : [ m...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_multiclass.html -
Common pitfalls in the interpretation of coeffi...
1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04,...ray([1.e-10, 1.e-09, 1.e-08, 1.e-07, 1.e-06, 1.e-05, 1.e-04,...scikit-learn.org/stable/auto_examples/inspection/plot_linear_model_coefficient_interpretation.html -
Release Highlights — scikit-learn 1.7.0 documen...
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...scikit-learn 1.7 Release Highlights for scikit-learn 1.7 Release...scikit-learn.org/stable/auto_examples/release_highlights/index.html -
SVM: Maximum margin separating hyperplane — sci...
levels = [ - 1 , 0 , 1 ], alpha = 0.5 , linestyles...support_vectors_ [:, 1 ], s = 100 , linewidth = 1 , facecolors = "none"...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane.html -
HuberRegressor vs Ridge on dataset with strong ...
) epsilon_values = [ 1 , 1.5 , 1.75 , 1.9 ] for k , epsilon in...n_samples = 20 , n_features = 1 , random_state = 0 , noise = 4.0...scikit-learn.org/stable/auto_examples/linear_model/plot_huber_vs_ridge.html -
Class Likelihood Ratios to measure classificati...
param to positive negative mean 1.0 1.0 std 0.0 0.0 The absence of...linspace ( 0.1 , 0.8 , 6 ) weights = weights [:: - 1 ] # fit and...scikit-learn.org/stable/auto_examples/model_selection/plot_likelihood_ratios.html