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recall_score — scikit-learn 1.7.2 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.recall_score.html -
silhouette_samples — scikit-learn 1.7.2 documen...
fit_predict ( X ) >>> silhouette_samples ( X , labels ) array([...]) Gallery...sklearn.metrics. silhouette_samples ( X , labels , * , metric = 'euclidean'...scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_samples.html -
mean_absolute_percentage_error — scikit-learn 1...
= [ 3 , - 0.5 , 2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>...[ - 1 , 1 ], [ 7 , - 6 ]] >>> y_pred = [[ 0 , 2 ], [ - 1 , 2...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_percentage_error.html -
make_pipeline — scikit-learn 1.7.2 documentation
Pipeline(steps=[('standardscaler', StandardScaler()), ('gaussiannb',...('gaussiannb', GaussianNB())]) Gallery examples # Time-related feature...scikit-learn.org/stable/modules/generated/sklearn.pipeline.make_pipeline.html -
TargetEncoder — scikit-learn 1.7.2 documentation
array ([[ "dog" ] * 20 + [ "cat" ] * 30 + [ "snake" ] * 38 ], dtype...encodings_[j + (i * len(classes_))] . E.g., for 2 features (f) and 3...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.TargetEncoder.html -
FeatureHasher — scikit-learn 1.7.2 documentation
, 0., 0., 0., 2.], [ 0., 0., 0., -2., -5., 0., 0., 0., 0., 0.]])...transform ( D ) >>> f . toarray () array([[ 0., 0., -4., -1., 0., 0.,...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
ExpSineSquared — scikit-learn 1.7.2 documentation
True ) (array([425.6, 457.5]), array([0.3894, 0.3467])) __call__...100000.0) , periodicity_bounds = (1e-05, 100000.0) ) [source] #...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ExpSineSquared.html -
Kernel — scikit-learn 1.7.2 documentation
diag ( self , X ): ... return np . ones ( X . shape [ 0 ]) ... def...self , X , Y = None ): ... if Y is None : ... Y = X ... return...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Kernel.html -
validation_curve — scikit-learn 1.7.2 documenta...
instead. E.g.: validation_curve(..., params={'groups': groups})...instance (e.g., GroupKFold ). Changed in version 1.6: groups can...scikit-learn.org/stable/modules/generated/sklearn.model_selection.validation_curve.html -
RandomizedSearchCV — scikit-learn 1.7.2 documen...
rank_test_score ‘rbf’ 0.1 0.80 … 1 ‘rbf’ 0.2 0.84 … 3 ‘rbf’ 0.3 0.70 … 2...“score_samples”, “predict”, “predict_proba”, “decision_function”, “transform”...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html