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accuracy_score — scikit-learn 1.8.0 docum...
1 ], [ 1 , 1 ]]), np . ones (( 2 , 2...= [ 0 , 2 , 1 , 3 ] >>> y_true = [ 0 , 1 , 2 , 3 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html -
MDS — scikit-learn 1.8.0 documentation
n_init will change from 4 to 1 in version 1.9. init {‘random’, ‘classical_mds’},...Added in version 1.8. Changed in version 1.10: The default value...scikit-learn.org/stable/modules/generated/sklearn.manifold.MDS.html -
inplace_csr_row_normalize_l1 — scikit-lea...
1 , 2 , 3 ]) >>> data = np . array ([ 1.0 , 2.0...0. ], [0. , 0. , 1. , 0. ], [0. , 0. , 0. , 1. ]]) On this page...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs_fast.inplace_csr_row_normaliz... -
1.3. Kernel ridge regression — scikit-lea...
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 -
ClusterMixin — scikit-learn 1.8.0 documen...
fit_predict ( X ) array([1, 1, 1]) fit_predict ( X , y = None...return self >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.base.ClusterMixin.html -
cluster_optics_dbscan — scikit-learn 1.8....
1, 1, 1]) Gallery examples # Demo of...>>> X = np . array ([[ 1 , 2 ], [ 2 , 5 ], [ 3 , 6 ], ......scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_dbscan.html -
make_sparse_uncorrelated — scikit-learn 1...
described in Celeux et al [1]. as: X ~ N ( 0 , 1 ) y ( X ) = X [:, 0...0 ] + 2 * X [:, 1 ] - 2 * X [:, 2 ] - 1.5 * X [:, 3 ] Only the...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_uncorrelated.html -
PartialDependenceDisplay — scikit-learn 1...
Added in version 1.1: Add the possibility to pass...display . plot ( pdp_lim = { 1 : ( - 1.38 , 0.66 )}) <...>...scikit-learn.org/stable/modules/generated/sklearn.inspection.PartialDependenceDisplay.html -
AgglomerativeClustering — scikit-learn 1....
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2...clustering . labels_ array([1, 1, 1, 0, 0, 0]) For a comparison...scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html -
Lasso — scikit-learn 1.8.0 documentation
1 ) >>> clf . fit ([[ 0 , 0 ], [ 1 , 1 ], [ 2...2 , 2 ]], [ 0 , 1 , 2 ]) Lasso(alpha=0.1) >>> print (...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html