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confusion_matrix — scikit-learn 1.7.1 documenta...
[ "ant" , "bird" , "cat" ]) array([[2, 0, 0], [0, 0, 1], [1, 0,...0 , 1 , 0 , 1 ], [ 1 , 1 , 1 , 0 ]) . ravel () . tolist () >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
accuracy_score — scikit-learn 1.7.1 documentation
accuracy_score ( np . array ([[ 0 , 1 ], [ 1 , 1 ]]), np . ones (( 2 , 2...y_pred = [ 0 , 2 , 1 , 3 ] >>> y_true = [ 0 , 1 , 2 , 3 ] >>> accuracy_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html -
lars_path — scikit-learn 1.7.1 documentation
random_state = 0 ... ) >>> true_coef array([ 0. , 0. , 0. , 97.9, 45.7])...method=’lasso’ is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha *...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path.html -
7.7. Kernel Approximation — scikit-learn 1.7.1 ...
1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...\left(K_{21} U_1 \Lambda^{-1}\right)^T \\&= K_{21} U_1 (\Lambda^{-1} \Lambda)...scikit-learn.org/stable/modules/kernel_approximation.html -
NearestNeighbors — scikit-learn 1.7.1 documenta...
neigh . radius_neighbors ( ... [[ 0 , 0 , 1.3 ]], 0.4 , return_distance...queries. algorithm {‘auto’, ‘ball_tree’, ‘kd_tree’, ‘brute’}, default=’auto’...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestNeighbors.html -
KNeighborsRegressor — scikit-learn 1.7.1 docume...
KNeighborsRegressor(...) >>> print ( neigh . predict ([[ 1.5 ]])) [0.5] fit...regression . algorithm {‘auto’, ‘ball_tree’, ‘kd_tree’, ‘brute’}, default=’auto’...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html -
Nystroem — scikit-learn 1.7.1 documentation
Nystroem ( gamma = .2 , ... random_state = 1 , ... n_components...LinearSVC() >>> clf . score ( data_transformed , y ) 0.9987... fit...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.Nystroem.html -
roc_auc_score — scikit-learn 1.7.1 documentation
{‘micro’, ‘macro’, ‘samples’, ‘weighted’} or None, default=’macro’ If...multiclass. multi_class {‘raise’, ‘ovr’, ‘ovo’}, default=’raise’ Only...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html -
PolynomialCountSketch — scikit-learn 1.7.1 docu...
1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...SGDClassifier(max_iter=10) >>> clf . score ( X_features , y ) 1.0 For...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.PolynomialCountSketch.html -
f1_score — scikit-learn 1.7.1 documentation
weights. zero_division {“warn”, 0.0, 1.0, np.nan}, default=”warn”...average {‘micro’, ‘macro’, ‘samples’, ‘weighted’, ‘binary’} or None,...scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html