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RBF SVM parameters — scikit-learn 1.8.0 d...
1 , 1e2 ] gamma_2d_range = [ 1e-1 , 1 , 1e1 ] classifiers...np.float64(1.0), 'gamma': np.float64(0.1)} with a score...scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html -
Examples of Using FrozenEstimator — sciki...
same three data points: [1 1 1] Now imagine you’d want to set...scikit-learn 1.5 Release Highlights for scikit-learn 1.5 Probability...scikit-learn.org/stable/auto_examples/frozen/plot_frozen_examples.html -
pair_confusion_matrix — scikit-learn 1.8....
1 , 1 ], [ 1 , 1 , 0 , 0 ]) array([[8,...pair_confusion_matrix ([ 0 , 0 , 1 , 2 ], [ 0 , 0 , 1 , 1 ]) array([[8, 2],...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.pair_confusion_matrix.html -
linear_kernel — scikit-learn 1.8.0 docume...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...linear_kernel ( X , Y ) array([[0., 0.], [1., 2.]]) On this page This Page...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.linear_kernel.html -
incr_mean_variance_axis — scikit-learn 1....
1 , 2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2...last_n = 2 ... ) (array([1.33, 0.167, 1.17]), array([8.88, 0.139,...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.incr_mean_variance_axis.html -
BiclusterMixin — scikit-learn 1.8.0 docum...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...np . ones ( shape = ( 1 , X . shape [ 1 ]), dtype = bool ) ......scikit-learn.org/stable/modules/generated/sklearn.base.BiclusterMixin.html -
get_scorer — scikit-learn 1.8.0 documenta...
1 , - 1 , - 0.5 , 2 ], ( - 1 , 1 )) >>>...>>> y = np . array ([ 0 , 1 , 1 , 0 , 1 ]) >>> classifier...scikit-learn.org/stable/modules/generated/sklearn.metrics.get_scorer.html -
calibration_curve — scikit-learn 1.8.0 do...
1 , 1 , 1 , 1 , 1 ]) >>> y_pred...positive class. Added in version 1.1. n_bins int, default=5 Number...scikit-learn.org/stable/modules/generated/sklearn.calibration.calibration_curve.html -
NuSVC — scikit-learn 1.8.0 documentation
array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>>...default=-1 Hard limit on iterations within solver, or -1 for no...scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVC.html -
mean_poisson_deviance — scikit-learn 1.8....
with the power parameter power=1 . Read more in the User Guide...>>> y_true = [ 2 , 0 , 1 , 4 ] >>> y_pred = [...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_poisson_deviance.html