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LassoCV — scikit-learn 1.8.0 documentation
since version 1.7: n_alphas was deprecated in 1.7 and will be...since version 1.7: alphas=None was deprecated in 1.7 and will be...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoCV.html -
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 -
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 -
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 -
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 -
mean_squared_log_error — scikit-learn 1.8...
1 ], [ 1 , 2 ], [ 7 , 6 ]] >>>...>>> y_pred = [[ 0.5 , 2 ], [ 1 , 2.5 ], [ 8 , 8 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_log_error.html -
d2_pinball_score — scikit-learn 1.8.0 doc...
Added in version 1.1. Parameters : y_true array-like...y_true = [ 1 , 2 , 3 ] >>> y_pred = [ 1 , 3 , 3 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_pinball_score.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... -
lars_path — scikit-learn 1.8.0 documentation
the case method=’lasso’ is: ( 1 / ( 2 * n_samples )) * || y -...equation (see discussion in [1] ). Read more in the User Guide...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path.html