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check_scoring — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub check_scoring # sklearn.metrics. check_scoring ( estimator = None , ...scikit-learn.org/stable/modules/generated/sklearn.metrics.check_scoring.html -
Linear and Quadratic Discriminant Analysis with...
0) and (1, 1) . Each blob is assigned a specific...cov_class_2 + np . array ([ 1 , 1 ]), ] ) y = np . concatenate...scikit-learn.org/stable/auto_examples/classification/plot_lda_qda.html -
Column Transformer with Mixed Types — scikit-le...
1 , 1.0 , 10 , 100 ], } search_cv...param_distributions={'classifier__C': [0.1, 1.0, 10, 100], 'preprocessor_...scikit-learn.org/stable/auto_examples/compose/plot_column_transformer_mixed_types.html -
Semi-supervised Classification on a Text Datase...
sum ( 1 for x in y_train if x == - 1 )) clf . fit (...training set: 1706 End of iteration 1, added 1076 new labels. End of...scikit-learn.org/stable/auto_examples/semi_supervised/plot_semi_supervised_newsgroups.html -
pairwise_kernels — scikit-learn 1.5.2 documenta...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.pairwise_kernels.html -
ward_tree — scikit-learn 1.5.2 documentation
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2...children ndarray of shape (n_nodes-1, 2) The children of each non-leaf...scikit-learn.org/stable/modules/generated/sklearn.cluster.ward_tree.html -
Robust covariance estimation and Mahalanobis di...
where feature 1 has a standard deviation equal to 1 and feature...np . arange ( 1 , n_features ), np . arange ( 1 , n_features )]...scikit-learn.org/stable/auto_examples/covariance/plot_mahalanobis_distances.html -
Color Quantization using K-Means — scikit-learn...
(need to # be in the range [0-1]) china = np . array ( china ,...random_state = 0 , n_samples = 1_000 ) kmeans = KMeans ( n_clusters...scikit-learn.org/stable/auto_examples/cluster/plot_color_quantization.html -
Decision Tree Regression — scikit-learn 1.5.2 d...
RandomState ( 1 ) X = np . sort ( 5 * rng . rand ( 80 , 1 ), axis =...0.01 )[:, np . newaxis ] y_1 = regr_1 . predict ( X_test ) y_2...scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html -
Plot classification probability — scikit-learn ...
shape [ 1 ] C = 10 kernel = 1.0 * RBF ([ 1.0 , 1.0 ]) # for...for { name } : { accuracy : 0.1% } " ) for label in np . unique...scikit-learn.org/stable/auto_examples/classification/plot_classification_probability.html