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BaggingRegressor — scikit-learn 1.6.1 documenta...
max_samples = 1.0 , max_features = 1.0 , bootstrap = True...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html -
clone — scikit-learn 1.6.1 documentation
>>> X = [[ - 1 , 0 ], [ 0 , 1 ], [ 0 , - 1 ], [ 1 , 0 ]] >>> y...y = [ 0 , 0 , 1 , 1 ] >>> classifier = LogisticRegression ()...scikit-learn.org/stable/modules/generated/sklearn.base.clone.html -
ARDRegression — scikit-learn 1.6.1 documentation
[ 1 , 1 ], [ 2 , 2 ]], [ 0 , 1 , 2 ]) ARDRegression()...>>> clf . predict ([[ 1 , 1 ]]) array([1.]) fit ( X , y ) [source]...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ARDRegression.html -
DecisionBoundaryDisplay — scikit-learn 1.6.1 do...
Added in version 1.1. Parameters : xx0 ndarray of...iris . data [:, 1 ] . min (), iris . data [:, 1 ] . max ()) ......scikit-learn.org/stable/modules/generated/sklearn.inspection.DecisionBoundaryDisplay.html -
SkewedChi2Sampler — scikit-learn 1.6.1 document...
[ 1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...SkewedChi2Sampler ( * , skewedness = 1.0 , n_components = 100 , random_state...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.SkewedChi2Sampler.html -
Feature transformations with ensembles of trees...
feature values for these leaves to 1 and the other feature values to..., 0.2 ) ax . set_ylim ( 0.8 , 1 ) _ = ax . set_title ( "ROC curve...scikit-learn.org/stable/auto_examples/ensemble/plot_feature_transformation.html -
trustworthiness — scikit-learn 1.6.1 documentation
1]. It is defined as \[T(k) = 1 - \frac{2}{nk (2n...(2n - 3k - 1)} \sum^n_{i=1} \sum_{j \in \mathcal{N}_{i}^{k}}...scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html -
PoissonRegressor — scikit-learn 1.6.1 documenta...
predict ([[ 1 , 1 ], [ 3 , 4 ]]) array([10.676...,...PoissonRegressor ( * , alpha = 1.0 , fit_intercept = True , solver...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PoissonRegressor.html -
DummyClassifier — scikit-learn 1.6.1 documentation
([ - 1 , 1 , 1 , 1 ]) >>> y = np . array ([ 0 , 1 , 1 , 1 ]) >>>...dummy_clf . predict ( X ) array([1, 1, 1, 1]) >>> dummy_clf . score (...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html -
GaussianMixture — scikit-learn 1.6.1 documentation
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], [ 10 , 2 ],...GaussianMixture ( n_components = 1 , * , covariance_type = 'full'...scikit-learn.org/stable/modules/generated/sklearn.mixture.GaussianMixture.html