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adjusted_mutual_info_score — scikit-learn 1.7.2...
JMLR [ 2 ] Wikipedia entry for the Adjusted...([ 0 , 0 , 0 , 0 ], [ 0 , 1 , 2 , 3 ]) 0.0 Gallery examples #...scikit-learn.org/stable/modules/generated/sklearn.metrics.adjusted_mutual_info_score.html -
5. Inspection — scikit-learn 1.7.2 documentation
2. Permutation feature importance 5.2.1. Outline of...permutation importance algorithm 5.2.2. Relation to impurity-based importance...scikit-learn.org/stable/inspection.html -
Restricted Boltzmann Machine features for digit...
2 , random_state = 0 ) Models definition...0.09s [BernoulliRBM] Iteration 2, pseudo-likelihood = -23.68, time...scikit-learn.org/stable/auto_examples/neural_networks/plot_rbm_logistic_classification.html -
weighted_mode — scikit-learn 1.7.2 documentation
2 , 4 , 2 ] >>> weights = [ 1 , 1 ,...weights ) (array([2.]), array([3.5])) The value 2 has the highest...scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.weighted_mode.html -
fbeta_score — scikit-learn 1.7.2 documentation
2 , 0 , 1 , 2 ] >>> y_pred = [ 0 , 2 , 1 , 0 , 0...\frac{(1 + \beta^2) \text{tp}} {(1 + \beta^2) \text{tp} + \text{fp}...scikit-learn.org/stable/modules/generated/sklearn.metrics.fbeta_score.html -
Kernel PCA — scikit-learn 1.7.2 documentation
subplots ( ncols = 2 , sharex = True , sharey = True...KernelPCA pca = PCA ( n_components = 2 ) kernel_pca = KernelPCA ( n_components...scikit-learn.org/stable/auto_examples/decomposition/plot_kernel_pca.html -
Adjustment for chance in clustering performance...
linspace ( 2 , n_samples , 10 ) . astype ( int ) plt . figure ( 2 ) plots...n_clusters_range = np . linspace ( 2 , 100 , 10 ) . astype ( int )...scikit-learn.org/stable/auto_examples/cluster/plot_adjusted_for_chance_measures.html -
class_likelihood_ratios — scikit-learn 1.7.2 do...
"LR-": value_2} where the values can be non-negative...scikit-learn.org/stable/modules/generated/sklearn.metrics.class_likelihood_ratios.html -
L1 Penalty and Sparsity in Logistic Regression ...
%s " % l1_ratio ) axes_row [ 2 ] . set_title ( "L2 penalty" )...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_l1_l2_sparsity.html -
k_means — scikit-learn 1.7.2 documentation
2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2 ], [ 10 , 4...>>> centroid array([[10., 2.], [ 1., 2.]]) >>> label array([1,...scikit-learn.org/stable/modules/generated/sklearn.cluster.k_means.html