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Binarizer — scikit-learn 1.8.0 documentation
( X ) array([[1., 0., 1.], [1., 0., 0.], [0., 1., 0.]]) fit (...= [[ 1. , - 1. , 2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , -...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Binarizer.html -
r2_score — scikit-learn 1.8.0 documentation
1 ], [ - 1 , 1 ], [ 7 , - 6 ]] >>>...cross-validation). Added in version 1.1. Returns : z float or ndarray...scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
MeanShift — scikit-learn 1.8.0 documentation
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . labels_ array([1, 1, 1, 0, 0, 0]) >>> clustering...scikit-learn.org/stable/modules/generated/sklearn.cluster.MeanShift.html -
ledoit_wolf_shrinkage — scikit-learn 1.8....
regularized (shrunk) covariance is: (1 - shrinkage) * cov + shrinkage...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf_shrinkage.html -
balanced_accuracy_score — scikit-learn 1....
1 , 0 , 0 , 1 , 0 ] >>> y_pred = [ 0 , 1 , 0 ,...each class. The best value is 1 and the worst value is 0 when...scikit-learn.org/stable/modules/generated/sklearn.metrics.balanced_accuracy_score.html -
2.3. Clustering — scikit-learn 1.8.0 docu...
1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2...0 , 1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2...scikit-learn.org/stable/modules/clustering.html -
MultiLabelBinarizer — scikit-learn 1.8.0 ...
fit_transform ([( 1 , 2 ), ( 3 ,)]) array([[1, 1, 0], [0, 0, 1]]) >>>...'comedy' }]) array([[0, 1, 1], [1, 0, 0]]) >>> list...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MultiLabelBinarizer.html -
KernelDensity — scikit-learn 1.8.0 docume...
log_density array([-1.52955942, -1.51462041, -1.60244657]) fit (...KernelDensity ( * , bandwidth = 1.0 , algorithm = 'auto' , kernel...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html -
QuadraticDiscriminantAnalysis — scikit-le...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
SVM: Weighted samples — scikit-learn 1.8....
n_clusters_per_class = 1 , class_sep = 1.1 , weights = [ 0.9 , 0.1 ], random_state...( X_plot [:, 0 ], X_plot [:, 1 ], c = y_plot , s = 100 * sample_weight...scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html