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chi2_kernel — scikit-learn 1.7.1 documentation
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...chi2_kernel ( X , Y = None , gamma = 1.0 ) [source] # Compute the exponential...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.chi2_kernel.html -
fbeta_score — scikit-learn 1.7.1 documentation
1 , 2 , 0 , 1 , 2 ] >>> y_pred = [ 0 , 2 , 1 , 0 , 0...beta > 1 gives more weight to recall, while beta < 1 favors precision....scikit-learn.org/stable/modules/generated/sklearn.metrics.fbeta_score.html -
partial_dependence — scikit-learn 1.7.1 documen...
[ 1 , 0 , 0 ]] >>> y = [ 0 , 1 ] >>> from sklearn.ensemble...interacting features (e.g. [(0, 1)] ) for which the partial dependency...scikit-learn.org/stable/modules/generated/sklearn.inspection.partial_dependence.html -
k_means — scikit-learn 1.7.1 documentation
[ 1., 2.]]) >>> label array([1, 1, 1, 0, 0, 0], dtype=int32)...X = np . array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2...scikit-learn.org/stable/modules/generated/sklearn.cluster.k_means.html -
linear_kernel — scikit-learn 1.7.1 documentation
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...linear_kernel ( X , Y ) array([[0., 0.], [1., 2.]]) On this page This Page...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.linear_kernel.html -
Selecting the number of clusters with silhouett...
from -1, 1 but in this example all # lie within [-0.1, 1] ax1...set_xlim ([ - 0.1 , 1 ]) # The (n_clusters+1)*10 is for inserting...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html -
sklearn.dummy — scikit-learn 1.7.1 documentation
Dummy estimators that implement simple rules of thumb. User guide. See the Metrics and scoring: quantifying the quality of predictions section for further details.scikit-learn.org/stable/api/sklearn.dummy.html -
sklearn.frozen — scikit-learn 1.7.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version sklearn.frozen # FrozenEstimator Estimator that wraps...scikit-learn.org/stable/api/sklearn.frozen.html -
sklearn.svm — scikit-learn 1.7.1 documentation
Support vector machine algorithms. User guide. See the Support Vector Machines section for further details.scikit-learn.org/stable/api/sklearn.svm.html -
Semi Supervised Classification — scikit-learn 1...
Examples concerning the sklearn.semi_supervised module. Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset Effect of varying threshold for self-training Label Propagati...scikit-learn.org/stable/auto_examples/semi_supervised/index.html