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PartialDependenceDisplay — scikit-learn 1...
Added in version 1.1: Add the possibility to pass...display . plot ( pdp_lim = { 1 : ( - 1.38 , 0.66 )}) <...>...scikit-learn.org/stable/modules/generated/sklearn.inspection.PartialDependenceDisplay.html -
shrunk_covariance — scikit-learn 1.8.0 do...
1 ) [source] # Calculate covariance...ndarray. shrinkage float, default=0.1 Coefficient in the convex combination...scikit-learn.org/stable/modules/generated/sklearn.covariance.shrunk_covariance.html -
compute_sample_weight — scikit-learn 1.8....
[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...instead of [{1:1}, {2:5}, {3:1}, {4:1}] . The "balanced"...scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_sample_weight.html -
top_k_accuracy_score — scikit-learn 1.8.0...
The best performance is 1 with normalize == True and the...>>> y_true = np . array ([ 0 , 1 , 2 , 2 ]) >>> y_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html -
adjusted_rand_score — scikit-learn 1.8.0 ...
1 , 1 ], [ 0 , 0 , 1 , 1 ]) 1.0 >>> adjusted_rand_score...adjusted_rand_score ([ 0 , 0 , 1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Labelings that...scikit-learn.org/stable/modules/generated/sklearn.metrics.adjusted_rand_score.html -
as_float_array — scikit-learn 1.8.0 docum...
Added in version 1.6: force_all_finite was renamed...array = np . array ([ 0 , 0 , 1 , 2 , 2 ], dtype = np . int64...scikit-learn.org/stable/modules/generated/sklearn.utils.as_float_array.html -
TimeSeriesSplit — scikit-learn 1.8.0 docu...
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [...index=[0] Test: index=[1] Fold 1: Train: index=[0 1] Test: index=[2]...scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html -
make_friedman2 — scikit-learn 1.8.0 docum...
1 ] <= 560 * pi , 0 <= X [:, 2 ] <= 1 , 1 <=...** 2 + ( X [:, 1 ] * X [:, 2 ] - 1 / ( X [:, 1 ] * X [:, 3 ]))...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman2.html -
empirical_covariance — scikit-learn 1.8.0...
>>> X = [[ 1 , 1 , 1 ],[ 1 , 1 , 1 ],[ 1 , 1 , 1 ], ... [ 0 ,...scikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html -
LocalOutlierFactor — scikit-learn 1.8.0 d...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...fit_predict ( X ) array([ 1, 1, -1, 1]) >>> clf . neg...scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html