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1.3. Kernel ridge regression — scikit-learn 1.6...
Ctrl + K GitHub Choose version 1.3. Kernel ridge regression # Kernel...model using only approximately 1/3 of the 100 training datapoints...scikit-learn.org/stable/modules/kernel_ridge.html -
Quantile regression — scikit-learn 1.6.1 docume...
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Lagged features...axs [ 1 , 0 ] . set_xlabel ( "Residuals" ) _ = axs [ 1 , 1 ] ....scikit-learn.org/stable/auto_examples/linear_model/plot_quantile_regression.html -
is_multilabel — scikit-learn 1.6.1 documentation
1 , 0 , 1 ]) False >>> is_multilabel ([[ 1 ], [ 0 ,...is_multilabel ( np . array ([[ 1 , 0 ], [ 0 , 0 ]])) True >>> is_multilabel...scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.is_multilabel.html -
Getting Started — scikit-learn 1.6.1 documentation
dataset is easy array([1., 1., 1., 1., 1.]) Automatic parameter...transform ( X ) array([[-1., 1.], [ 1., -1.]]) Sometimes, you want...scikit-learn.org/stable/getting_started.html -
CompoundKernel — scikit-learn 1.6.1 documentation
theta ) [1.09861229 0.69314718] __call__...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.CompoundKernel.html -
Principal Component Analysis (PCA) on Iris Data...
figure ( 1 , figsize = ( 8 , 6 )) ax = fig...X_reduced [:, 0 ], X_reduced [:, 1 ], X_reduced [:, 2 ], c = iris...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_iris.html -
Release Highlights for scikit-learn 1.5 — sciki...
array([[-1.1, 1.1, 1.1], [ 3.9, -1.2, 1.1], [ 0.1, 1.3, 1.1], [-0.1,...[-0.1, -1.4, -1.4], [-4.9, 1.5, -1.5], [ 0.1, 1.6, 1.6]]) Pairwise...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html -
Release Highlights for scikit-learn 1.3 — sciki...
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...array ([ 0 , 1 , 6 , np . nan ]) . reshape ( - 1 , 1 ) y = [ 0 ,...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_3_0.html -
Release Highlights for scikit-learn 1.4 — sciki...
0 1.0 0.862662 1.0 0.0 1.401826 0.0 1.0 -0.754829 1.0 0.0...array ([ 0 , 1 , 6 , np . nan ]) . reshape ( - 1 , 1 ) y = [ 0 ,...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_4_0.html -
EmpiricalCovariance — scikit-learn 1.6.1 docume...
scikit-learn.org/stable/modules/generated/sklearn.covariance.EmpiricalCovariance.html