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incr_mean_variance_axis — scikit-learn 1....
2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2 , 5...>>> scale = np . array ([ 2 , 3 , 2 ]) >>> csr = sparse...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.incr_mean_variance_axis.html -
gen_batches — scikit-learn 1.8.0 documentation
list ( gen_batches ( 2 , 3 )) [slice(0, 2, None)] >>> list ( gen_batches...gen_batches ( 7 , 3 , min_batch_size = 2 )) [slice(0, 3, None), slice(3,...scikit-learn.org/stable/modules/generated/sklearn.utils.gen_batches.html -
mean_absolute_percentage_error — scikit-learn 1...
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>> m...1. , 0. , 2.4 , 7. ] >>> y_pred = [ 1.2 , 0.1 , 2.4 , 8. ] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_percentage_error.html -
Principal Component Regression vs Partial Least...
n_samples ) / 2 fig , axes = plt . subplots ( 1 , 2 , figsize =...) pca = PCA ( n_components = 2 ) . fit ( X ) plt . scatter (...scikit-learn.org/stable/auto_examples/cross_decomposition/plot_pcr_vs_pls.html -
train_test_split — scikit-learn 1.8.0 documenta...
2 1 4.9 3.0 1.4 0.2 2 4.7 3.2 1.3 0.2 3 4.6 3.1 1.5...1.4 0.2 122 7.7 2.8 6.7 2.0 >>> y_train . head () 96 1 105 2 66...scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html -
indexable — scikit-learn 1.8.0 documentation
2 , 3 ], np . array ([ 2 , 3 , 4 ]), None ,...indexable ( * iterables ) [[1, 2, 3], array([2, 3, 4]), None, <...Sparse...dtype...scikit-learn.org/stable/modules/generated/sklearn.utils.indexable.html -
resample — scikit-learn 1.8.0 documentation
2)> >>> X_sparse . toarray () array([[1., 0.], [2., 1.],...= np . array ([[ 1. , 0. ], [ 2. , 1. ], [ 0. , 0. ]]) >>> y =...scikit-learn.org/stable/modules/generated/sklearn.utils.resample.html -
Comparison of LDA and PCA 2D projection of Iris...
the different samples on the 2 first principal components. Linear...target_names pca = PCA ( n_components = 2 ) X_r = pca . fit ( X ) . transform...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_vs_lda.html -
MultiTaskLasso — scikit-learn 1.8.0 documentation
2 ], [ 2 , 4 ]], [[ 0 , 0 ], [ 1 , 1 ], [ 2 , 3 ]]) ...Lasso is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ 2 _Fro + alpha...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLasso.html -
Face completion with a multi-output estimators ...
n_pixels // 2 :] X_test = test [:, : ( n_pixels + 1 ) // 2 ] y_test.... figure ( figsize = ( 2.0 * n_cols , 2.26 * n_faces )) plt ....scikit-learn.org/stable/auto_examples/miscellaneous/plot_multioutput_face_completion.html