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l1_min_c — scikit-learn 1.8.0 documentation
intercept_scaling = 1.0 ) [source] # Return the lowest...sticRegression with l1_ratio=1 . This value is valid if class_weight...scikit-learn.org/stable/modules/generated/sklearn.svm.l1_min_c.html -
permutation_test_score — scikit-learn 1.8...
p-value is 1/(n_permutations + 1), the worst is 1.0. Notes This...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.model_selection.permutation_test_score.html -
additive_chi2_kernel — scikit-learn 1.8.0...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...additive_chi2_kernel ( X , Y ) array([[-1., -2.], [-2., -1.]]) On this page This...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.additive_chi2_kernel.html -
make_hastie_10_2 — scikit-learn 1.8.0 doc...
float64(-1.0), np.float64(1.0), np.float64(-1.0), np.float64(1.0),...i ] = 1 if np . sum ( X [ i ] ** 2 ) > 9.34 else - 1 Read more...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_hastie_10_2.html -
MinMaxScaler — scikit-learn 1.8.0 documen...
data = [[ - 1 , 2 ], [ - 0.5 , 6 ], [ 0 , 10 ], [ 1 , 18 ]] >>>...0. ] [0.25 0.25] [0.5 0.5 ] [1. 1. ]] >>> print ( scaler...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html -
Iso-probability lines for Gaussian Processes cl...
1 , ( 1e-5 , np . inf )) * DotProduct ( sigma_0 = 0.1 ) **...not)""" return 5.0 - x [:, 1 ] - 0.5 * x [:, 0 ] ** 2.0 # Design...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_isoprobability.html -
ParameterGrid — scikit-learn 1.8.0 docume...
'a' : 1 , 'b' : True }, { 'a' : 1 , 'b'...param_grid = { 'a' : [ 1 , 2 ], 'b' : [ True ,...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterGrid.html -
Normalizer — scikit-learn 1.8.0 documenta...
1 , 2 , 2 ], ... [ 1 , 3 , 9 , 3 ], ... [...0.4, 0.4], [0.1, 0.3, 0.9, 0.3], [0.5, 0.7, 0.5, 0.1]]) fit ( X...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Normalizer.html -
KFold — scikit-learn 1.8.0 documentation
3] Test: index=[0 1] Fold 1: Train: index=[0 1] Test: index=[2...X = np . array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]])...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html -
dcg_score — scikit-learn 1.8.0 documentation
asarray ([[ 1 , 0 , 0 , 0 , 1 ]]) >>> # by...to have a score between 0 and 1. References Wikipedia entry for...scikit-learn.org/stable/modules/generated/sklearn.metrics.dcg_score.html