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DummyRegressor — scikit-learn 1.7.2 documentation
X = np . array ([ 1.0 , 2.0 , 3.0 , 4.0 ]) >>> y = np . array...array ([ 2.0 , 3.0 , 5.0 , 10.0 ]) >>> dummy_regr = DummyRegressor...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyRegressor.html -
precision_recall_curve — scikit-learn 1.7.2 doc...
66666667, 0.5 , 1. , 1. ]) >>> recall array([1. , 1. , 0.5, 0.5, 0....0. ]) >>> thresholds array([0.1 , 0.35, 0.4 , 0.8 ]) Gallery...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_curve.html -
RegressorMixin — scikit-learn 1.7.2 documentation
estimator . fit ( X , y ) . predict ( X ) array([0, 0, 0]) >>> estimator...of squares ((y_true - y_true.mean()) ** 2).sum() . The best possible...scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html -
MetaEstimatorMixin — scikit-learn 1.7.2 documen...
, X , y = None ): ... if self . estimator is None : ... self...self . estimator_ = LogisticRegression () ... else : ... self . estimator_...scikit-learn.org/stable/modules/generated/sklearn.base.MetaEstimatorMixin.html -
plot_multi_metric_evaluation.rst.txt
for sample, style in (("train", "--"), ("test", "-")): sample_score_mean...plt.ylabel("Score") ax = plt.gca() ax.set_xlim(0, 402) ax.set_ylim(0.73,...scikit-learn.org/stable/_sources/auto_examples/model_selection/plot_multi_metric_evaluation.rst.txt -
Nearest Neighbors — scikit-learn 1.7.2 document...
Factor (LOF) Novelty detection with Local Outlier Factor (LOF) Outlier...Factor (LOF) Outlier detection with Local Outlier Factor (LOF) Simple...scikit-learn.org/stable/auto_examples/neighbors/index.html -
StackingClassifier — scikit-learn 1.7.2 documen...
RandomForestClassifi ( n_estimators = 10 , random_state = 42 )), ... ( 'svr' ,...load_iris ( return_X_y = True ) >>> estimators = [ ... ( 'rf' , RandomForestClassifi...scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingClassifier.html -
StackingRegressor — scikit-learn 1.7.2 document...
RidgeCV ()), ... ( 'svr' , LinearSVR ( random_state = 42 )) ... ] >>>...X_test , y_test ) 0.3... fit ( X , y , ** fit_params ) [source] #...scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingRegressor.html -
load_diabetes — scikit-learn 1.7.2 documentation
load_diabetes () >>> diabetes . target [: 3 ] array([151., 75., 141.]) >>>...diabetes . data . shape (442, 10) Gallery examples # Model Complexity...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_diabetes.html -
permutation_importance — scikit-learn 1.7.2 doc...
9 , 9 ],[ 1 , 9 , 9 ],[ 1 , 9 , 9 ], ... [ 0 , 9 , 9 ],[ 0 , 9...9 , 9 ],[ 0 , 9 , 9 ]] >>> y = [ 1 , 1 , 1 , 0 , 0 , 0 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.inspection.permutation_importance.html