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PLSSVD — scikit-learn 1.8.0 documentation
1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 , 5.9...np . array ([[ 0. , 0. , 1. ], ... [ 1. , 0. , 0. ], ... [ 2. ,...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html -
LocalOutlierFactor — scikit-learn 1.8.0 documen...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...fit_predict ( X ) array([ 1, 1, -1, 1]) >>> clf . negative_outlier_factor_...scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html -
empirical_covariance — scikit-learn 1.8.0 docum...
>>> X = [[ 1 , 1 , 1 ],[ 1 , 1 , 1 ],[ 1 , 1 , 1 ], ... [ 0 ,...scikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html -
RANSACRegressor — scikit-learn 1.8.0 documentation
min_samples int (>= 1) or float ([0, 1]), default=None Minimum...min_samples is chosen as X.shape[1] + 1 . This parameter is highly...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RANSACRegressor.html -
contingency_matrix — scikit-learn 1.8.0 documen...
labels_pred ) array([[1, 1, 0], [0, 1, 1], [1, 0, 1]]) On this page..., 0 , 1 , 1 , 2 , 2 ] >>> labels_pred = [ 1 , 0 , 2 , 1 , 0 ,...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.contingency_matrix.html -
RationalQuadratic — scikit-learn 1.8.0 document...
RationalQuadratic ( length_scale = 1.0 , alpha = 1.0 , length_scale_bounds...RationalQuadratic ( length_scale = 1.0 , alpha = 1.5 ) >>> gpc = GaussianProcessClass...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RationalQuadratic.html -
ShuffleSplit — scikit-learn 1.8.0 documentation
array ([ 1 , 2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Train: index=[1 3 0 4] Test: index=[5 2] Fold 1: Train: index=[4...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
cosine_distances — scikit-learn 1.8.0 documenta...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...cosine_distances ( X , Y ) array([[1. , 1. ], [0.422, 0.183]]) On this...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_distances.html -
DistanceMetric — scikit-learn 1.8.0 documentation
get_metric ( 'euclidean' ) >>> X = [[ 1 , 2 ], [ 3 , 4 ], [ 5 , 6 ]] >>>...10.63...] [5.65..., 8.48...] [1.41..., 4.24...]]) Available Metrics...scikit-learn.org/stable/modules/generated/sklearn.metrics.DistanceMetric.html -
cluster_optics_xi — scikit-learn 1.8.0 document...
1, 1, 1]) >>> clusters array([[0, 2],...min_samples int > 1 or float between 0 and 1 The same as the min_samples...scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_xi.html