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Probability Calibration curves — scikit-learn 1...
0 ), ( 2 , 1 ), ( 3 , 0 ), ( 3 , 1 )] for i , ( _ , name ) in..., "Logistic" ), ( gnb , "Naive Bayes" ), ( gnb_isotonic , "Naive...scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html -
Prediction Intervals for Gradient Boosting Regr...
atleast_2d ( rng . uniform ( 0 , 10.0 , size = 1000 )) . T expected_y...alpha=0.05, 0.5, 0.95. The models obtained for alpha=0.05 and alpha=0.95...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_quantile.html -
Robust covariance estimation and Mahalanobis di...
06695631e-03 1.22747343e+00]] MLE: [[ 3.23773583 -0.24640578] [-0.24640578...\[d_{(\mu,\Sigma)}(x_i)^2 = (x_i - \mu)^T\Sigma^{-1}(x_i - \mu)\]...scikit-learn.org/stable/auto_examples/covariance/plot_mahalanobis_distances.html -
Release Highlights for scikit-learn 1.3 — sciki...
np . array ([ 0 , 1 , 6 , np . nan ]) . reshape ( - 1 , 1 ) y...random_state = 0 ) . fit ( X , y ) tree . predict ( X ) array([0, 0, 1, 1])...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_3_0.html -
smacof — scikit-learn 1.7.2 documentation
= np . array ([[ 0 , 1 , 2 ], [ 1 , 0 , 3 ], [ 2 , 3 , 0 ]]) >>>...of 0 indicates “perfect” fit, 0.025 excellent, 0.05 good, 0.1...scikit-learn.org/stable/modules/generated/sklearn.manifold.smacof.html -
Product — scikit-learn 1.7.2 documentation
score ( X , y ) 1.0 >>> kernel 1.41**2 * RBF(length_scale=1) __call__...kernel , ... random_state = 0 ) . fit ( X , y ) >>> gpr . score...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Product.html -
UndefinedMetricWarning — scikit-learn 1.7.2 doc...
Changed in version 0.18: Moved from sklearn.base. On this page This...exception sklearn.exceptions. UndefinedMetricWarni [source] # Warning...scikit-learn.org/stable/modules/generated/sklearn.exceptions.UndefinedMetricWarning.html -
sklearn.kernel_approximation — scikit-learn 1.7...
"skewed chi-squared" kernel....Back to top Ctrl + K GitHub Choose version sklearn.kernel_approximation...scikit-learn.org/stable/api/sklearn.kernel_approximation.html -
Clustering text documents using k-means — sciki...
= [ "alt.atheism" , "talk.religion.misc" , "comp.graphics" , "sci.space"..."headers" , "footers" , "quotes" ), subset = "all" , categories...scikit-learn.org/stable/auto_examples/text/plot_document_clustering.html -
One-class SVM with non-linear kernel (RBF) — sc...
1 , 1 ), yy . reshape ( - 1 , 1 )], axis = 1 ) DecisionBoundaryDisp...linspace ( - 5 , 5 , 10 )) X = np . concatenate ([ xx . reshape ( - 1...scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html