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load_iris — scikit-learn 1.7.1 documentation
data . target [[ 10 , 25 , 50 ]] array([0, 0, 1]) >>> list ( data...data . target_names ) [np.str_('setosa'), np.str_('versicolor'),...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html -
governance.rst.txt
way, they are a contributor. Core Contributors ---------- All...relevant to their roles. Contributors ---------- Contributors are community...scikit-learn.org/stable/_sources/governance.rst.txt -
MinCovDet — scikit-learn 1.7.1 documentation
real_cov = np . array ([[ .8 , .3 ], ... [ .3 , .4 ]]) >>> rng =...>>> cov . covariance_ array([[0.7411, 0.2535], [0.2535, 0.3053]])...scikit-learn.org/stable/modules/generated/sklearn.covariance.MinCovDet.html -
config_context — scikit-learn 1.7.1 documentation
print ‘SVC()’, but would print ‘SVC(C=1.0, cache_size=200, …)’...float ( 'nan' )]) Traceback (most recent call last): ... ValueError...scikit-learn.org/stable/modules/generated/sklearn.config_context.html -
mutual_info_score — scikit-learn 1.7.1 document...
= [ 0 , 1 , 1 , 0 , 1 , 0 ] >>> labels_pred = [ 0 , 1 , 0 , 0...switching \(U\) (i.e label_true ) with \(V\) (i.e. label_pred ) will...scikit-learn.org/stable/modules/generated/sklearn.metrics.mutual_info_score.html -
EmpiricalCovariance — scikit-learn 1.7.1 docume...
covariance_ array([[0.7569, 0.2818], [0.2818, 0.3928]]) >>> cov . location_...sqrt(tr(A^t.A)) - ‘spectral’: sqrt(max(eigenvalues(A^t.A)) where...scikit-learn.org/stable/modules/generated/sklearn.covariance.EmpiricalCovariance.html -
make_column_transformer — scikit-learn 1.7.1 do...
er ( ... ( StandardScaler (), [ 'numerical_column' ]), ... (...['numerical_column']), ('onehotencoder', OneHotEncoder(...), ['categorical_column'])])...scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_transformer.html -
RegressorMixin — scikit-learn 1.7.1 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 -
normalized_mutual_info_score — scikit-learn 1.7...
fo_score ([ 0 , 0 , 1 , 1 ], [ 0 , 0 , 1 , 1 ]) 1.0 >>> norm...fo_score ([ 0 , 0 , 1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 If classes...scikit-learn.org/stable/modules/generated/sklearn.metrics.normalized_mutual_info_score.html -
IsolationForest — scikit-learn 1.7.1 documentation
max_samples = 'auto' , contamination = 'auto' , max_features = 1.0 , bootstrap...from 0.1 to 'auto' . max_features int or float, default=1.0 The...scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html