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non_negative_factorization — scikit-learn...
||H||_{Fro}^2,\end{aligned}\end{align} \] where \(||A||_{Fro}^2 = \sum_{i,j}...array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...scikit-learn.org/stable/modules/generated/sklearn.decomposition.non_negative_factorization.html -
7.8. Pairwise metrics, Affinities and Kernels &...
for all a and b 2. d ( a , b ) == 0 , if and only...>>> X = np . array ([[ 2 , 3 ], [ 3 , 5 ], [ 5 , 8 ]])...scikit-learn.org/stable/modules/metrics.html -
Rastreo de Almacén de Datos
2,タイトル 2,テスト2です。 3,タイトル 3,テスト3です。 4,タイトル...VALUES ( 'タイトル 2' , 'コンテンツ 2 です．' , '34.701909'...fess.codelibs.org/es/15.3/admin/dataconfig-guide.html -
PassiveAggressiveRegressor — scikit-learn...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...[1, n_features] if n_classes == 2 else [n_classes, n_features] Weights...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PassiveAggressiveRegressor.html -
roc_auc_score — scikit-learn 1.8.0 docume...
the standardized partial AUC [2] over the range [0, max_fpr] is...under of the ROC as follows: G = 2 * AUC - 1 Where G is the Gini...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html -
mean_absolute_error — scikit-learn 1.8.0 ...
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>...>>> 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...
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>...>>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html -
One-Class SVM versus One-Class SVM using Stocha...
2 ) X_train = np . r_ [ X + 2 , X - 2 ] # Generate...randn ( 20 , 2 ) X_test = np . r_ [ X + 2 , X - 2 ] # Generate...scikit-learn.org/stable/auto_examples/linear_model/plot_sgdocsvm_vs_ocsvm.html -
lars_path — scikit-learn 1.8.0 documentation
float64(2.220446049250313e-16) , copy_Gram...case method=’lasso’ is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path.html -
multilabel_confusion_matrix — scikit-lear...
2]], [[5, 0], [1, 0]], [[2, 1], [1, 2]]]) On this...ndarray of shape (n_outputs, 2, 2) A 2x2 confusion matrix corresponding...scikit-learn.org/stable/modules/generated/sklearn.metrics.multilabel_confusion_matrix.html