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check_is_fitted — scikit-learn 1.8.0 documentation
fit ([[ 1 , 2 ], [ 1 , 3 ]], [ 1 , 0 ]) LogisticRegression()...scikit-learn.org/stable/modules/generated/sklearn.utils.validation.check_is_fitted.html -
oas — scikit-learn 1.8.0 documentation
References [ 1 ] ( 1 , 2 ) “Shrinkage algorithms...The regularised covariance is: (1 - shrinkage) * cov + shrinkage...scikit-learn.org/stable/modules/generated/oas-function.html -
mean_absolute_error — scikit-learn 1.8.0 docume...
1 ], [ - 1 , 1 ], [ 7 , - 6 ]] >>> y_pred...y_pred = [[ 0 , 2 ], [ - 1 , 2 ], [ 8 , - 5 ]] >>> mean_absolute_error...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html -
mean_squared_error — scikit-learn 1.8.0 documen...
1 ],[ - 1 , 1 ],[ 7 , - 6 ]] >>> y_pred...y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>> mean_squared_error...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html -
ParameterGrid — scikit-learn 1.8.0 documentation
[{ 'a' : 1 , 'b' : True }, { 'a' : 1 , 'b' : False },...( grid )[ 1 ] == { 'kernel' : 'rbf' , 'gamma' : 1 } True On this...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterGrid.html -
QuadraticDiscriminantAnalysis — scikit-learn 1....
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
manhattan_distances — scikit-learn 1.8.0 docume...
]]) array([[1.]]) >>> manhattan_distances ([[ 1 , 2 ], [ 3 ,...manhattan_distances ([[ 3 ]], [[ 2 ]]) array([[1.]]) >>> manhattan_distances ([[...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.manhattan_distances.html -
GammaRegressor — scikit-learn 1.8.0 documentation
alpha = 1.0 , fit_intercept = True , solver...Parameters : alpha float, default=1 Constant that multiplies the L2...scikit-learn.org/stable/modules/generated/sklearn.linear_model.GammaRegressor.html -
make_classification — scikit-learn 1.8.0 docume...
class_sep = 1.0 , hypercube = True , shift = 0.0 , scale = 1.0 , shuffle...[np.int64(0), np.int64(0), np.int64(1), np.int64(1), np.int64(0)] Gallery...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_classification.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