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check_array — scikit-learn 1.8.0 document...
ensure_min_samples = 1 , ensure_min_features = 1 , estimator = None...documentation. Added in version 1.1.0. Returns : array_converted...scikit-learn.org/stable/modules/generated/sklearn.utils.check_array.html -
mean_absolute_error — scikit-learn 1.8.0 ...
1 ], [ - 1 , 1 ], [ 7 , - 6 ]] >>>...>>> y_pred = [[ 0 , 2 ], [ - 1 , 2 ], [ 8 , - 5 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html -
mean_squared_error — scikit-learn 1.8.0 d...
1 ],[ - 1 , 1 ],[ 7 , - 6 ]] >>>...>>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html -
manhattan_distances — scikit-learn 1.8.0 ...
array([[1.]]) >>> manhattan_distances ([[ 1 , 2 ], [...manhattan_distances ([[ 3 ]], [[ 2 ]]) array([[1.]]) >>> manhattan_distances...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.manhattan_distances.html -
enet_path — scikit-learn 1.8.0 documentation
1.120, 0.620], [-0., -2.129, -1.128], [ 0., 23.046,...For mono-output tasks it is: 1 / ( 2 * n_samples ) * || y - Xw...scikit-learn.org/stable/modules/generated/sklearn.linear_model.enet_path.html -
r_regression — scikit-learn 1.8.0 documen...
Added in version 1.1. Returns : correlation_coefficient...User Guide . Added in version 1.0. Parameters : X {array-like,...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.r_regression.html -
SGDRegressor — scikit-learn 1.8.0 documen...
<= 1. l1_ratio=0 corresponds to L2 penalty, l1_ratio=1 to L1....passive-aggressive algorithm 1, see [1] . Only with loss='epsilon_insensitive'...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDRegressor.html -
LinearSVC — scikit-learn 1.8.0 documentation
version 1.3: The "auto" option is added in version 1.3 and...intercept term: [x_1, ..., x_n, 1] , where 1 corresponds to the intercept....scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html -
SpectralCoclustering — scikit-learn 1.8.0...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . row_labels_ array([0, 1, 1, 0, 0, 0], dtype=int32) >>>...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralCoclustering.html -
FastICA on 2D point clouds — scikit-learn...
array ([[ 1 , 1 ], [ 0 , 2 ]]) # Mixing matrix...( 42 ) S = rng . standard_t ( 1.5 , size = ( 20000 , 2 )) S [:,...scikit-learn.org/stable/auto_examples/decomposition/plot_ica_vs_pca.html