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Plot classification probability — scikit-learn ...
GaussianProcessClass ( kernel = 1.0 * RBF ([ 1.0 , 1.0 ])), "Logistic regression...LogisticRegression ( C = 0.1 ), "Logistic regression \n (C=1)" : LogisticRegression...scikit-learn.org/stable/auto_examples/classification/plot_classification_probability.html -
QuantileTransformer — scikit-learn 1.8.0 docume...
Added in version 1.5: The option None to disable...all strings. Added in version 1.0. See also quantile_transform...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.QuantileTransformer.html -
check_increasing — scikit-learn 1.8.0 documenta...
y = [ 1 , 2 , 3 , 4 , 5 ], [ 2 , 4 , 6...scikit-learn.org/stable/modules/generated/sklearn.isotonic.check_increasing.html -
ledoit_wolf_shrinkage — scikit-learn 1.8.0 docu...
regularized (shrunk) covariance is: (1 - shrinkage) * cov + shrinkage...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf_shrinkage.html -
precision_recall_curve — scikit-learn 1.8.0 doc...
y_true is in {-1, 1} or {0, 1}, pos_label is set to 1, otherwise...0.66666667, 0.5 , 1. , 1. ]) >>> recall array([1. , 1. , 0.5, 0.5,...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_curve.html -
make_friedman3 — scikit-learn 1.8.0 documentation
1 ] <= 560 * pi , 0 <= X [:, 2 ] <= 1 , 1 <= X [:, 3...arctan (( X [:, 1 ] * X [:, 2 ] - 1 / ( X [:, 1 ] * X [:, 3 ]))...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman3.html -
fetch_olivetti_faces — scikit-learn 1.8.0 docum...
Added in version 1.5. delay float, default=1.0 Number of seconds...False , n_retries = 3 , delay = 1.0 ) [source] # Load the Olivetti...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_olivetti_faces.html -
homogeneity_score — scikit-learn 1.8.0 document...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Non-perfect labelings...homogeneity_score ([ 0 , 0 , 1 , 1 ], [ 0 , 0 , 1 , 2 ])) 1.000000 >>> print...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_score.html -
maxabs_scale — scikit-learn 1.8.0 documentation
1 , 2 ], [ - 1 , 0 , 1 ]] >>> maxabs_scale...column independently array([[-1. , 1. , 1. ], [-0.5, 0. , 0.5]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html -
GMM covariances — scikit-learn 1.8.0 documentation
shape [ 1 ]) * gmm . covariances_ [ n ]...]) angle = np . arctan2 ( u [ 1 ], u [ 0 ]) angle = 180 * angle...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_covariances.html