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LabelEncoder — scikit-learn 1.7.1 documentation
"tokyo" , "tokyo" , "paris" ]) array([2, 2, 1]...) >>> list ( le ....2 , 6 ]) array([0, 0, 1, 2]...) >>> le . inverse_transform ([...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html -
f_regression — scikit-learn 1.7.1 documentation
array([1.21, 2.67e13, 2.66]) >>> p_values array([0.276, 1.54e-283,...as: E [( X [:, i ] - mean ( X [:, i ])) * ( y - mean ( y ))] / (...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_regression.html -
cluster_optics_dbscan — scikit-learn 1.7.1 docu...
, ... metric = "minkowski" , ... p = 2 , ... metric_params =...None , ... algorithm = "auto" , ... leaf_size = 30 , ... n_jobs...scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_dbscan.html -
contingency_matrix — scikit-learn 1.7.1 documen...
labels_pred ) array([[1, 1, 0], [0, 1, 1], [1, 0, 1]]) On this page This...= [ 0 , 0 , 1 , 1 , 2 , 2 ] >>> labels_pred = [ 1 , 0 , 2 , 1...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.contingency_matrix.html -
ledoit_wolf_shrinkage — scikit-learn 1.7.1 docu...
= np . array ([[ .4 , .2 ], [ .2 , .8 ]]) >>> rng = np . random...shrinkage) * cov + shrinkage * mu * np.identity(n_features) where...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf_shrinkage.html -
calinski_harabasz_score — scikit-learn 1.7.1 do...
calinski_harabasz_score ( X , kmeans . labels_ ) 114.8... On this page This...n_clusters = 3 , random_state = 0 ,) . fit ( X ) >>> calinski_harabasz_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.calinski_harabasz_score.html -
isotonic_regression — scikit-learn 1.7.1 docume...
, 2.75 , 2.75 , 2.75 , 7.33, 7.33, 7.33, 7.33, 7.33, 7.33]) On...isotonic_regression ([ 5 , 3 , 1 , 2 , 8 , 10 , 7 , 9 , 6 , 4 ]) array([2.75 ,...scikit-learn.org/stable/modules/generated/sklearn.isotonic.isotonic_regression.html -
check_increasing — scikit-learn 1.7.1 documenta...
3 , 4 , 5 ], [ 2 , 4 , 6 , 8 , 10 ] >>> check_increasing ( x...transformation. Wikipedia. https://en.wikipedia.org/wiki/Fisher_transformation...scikit-learn.org/stable/modules/generated/sklearn.isotonic.check_increasing.html -
murmurhash3_32 — scikit-learn 1.7.1 documentation
from -(2 ** 31) to 2 ** 31 - 1 Examples >>> from sklearn.utils...sklearn.utils. murmurhash3_32 ( key , seed = 0 , positive = False ) # Compute...scikit-learn.org/stable/modules/generated/sklearn.utils.murmurhash3_32.html -
LabelSpreading — scikit-learn 1.7.1 documentation
label_prop_model . fit ( iris . data , labels ) LabelSpreading(...) fit (...rand ( len ( iris . target )) < 0.3 >>> labels = np . copy ( iris...scikit-learn.org/stable/modules/generated/sklearn.semi_supervised.LabelSpreading.html