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SpectralClustering — scikit-learn 1.6.0 documen...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . labels_ array([1, 1, 1, 0, 0, 0]) >>> clustering ...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralClustering.html -
PLSSVD — scikit-learn 1.6.0 documentation
1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 , 5.9...version 1.5: Y is deprecated in 1.5 and will be removed in 1.7. Use...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html -
ARDRegression — scikit-learn 1.6.0 documentation
[ 1 , 1 ], [ 2 , 2 ]], [ 0 , 1 , 2 ]) ARDRegression()...>>> clf . predict ([[ 1 , 1 ]]) array([1.]) fit ( X , y ) [source]...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ARDRegression.html -
clone — scikit-learn 1.6.0 documentation
>>> X = [[ - 1 , 0 ], [ 0 , 1 ], [ 0 , - 1 ], [ 1 , 0 ]] >>> y...y = [ 0 , 0 , 1 , 1 ] >>> classifier = LogisticRegression ()...scikit-learn.org/stable/modules/generated/sklearn.base.clone.html -
DecisionBoundaryDisplay — scikit-learn 1.6.0 do...
Added in version 1.1. Parameters : xx0 ndarray of...iris . data [:, 1 ] . min (), iris . data [:, 1 ] . max ()) ......scikit-learn.org/stable/modules/generated/sklearn.inspection.DecisionBoundaryDisplay.html -
OneVsOneClassifier — scikit-learn 1.6.0 documen...
1, 0, 2, 0, 2, 0, 1, 1, 1]) decision_function...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsOneClassifier.html -
SkewedChi2Sampler — scikit-learn 1.6.0 document...
[ 1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...SkewedChi2Sampler ( * , skewedness = 1.0 , n_components = 100 , random_state...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.SkewedChi2Sampler.html -
SGDRegressor — scikit-learn 1.6.0 documentation
l1_ratio <= 1. l1_ratio=0 corresponds to L2 penalty, l1_ratio=1 to L1....True , verbose = 0 , epsilon = 0.1 , random_state = None , learning_rate...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDRegressor.html -
trustworthiness — scikit-learn 1.6.0 documentation
1]. It is defined as \[T(k) = 1 - \frac{2}{nk (2n...(2n - 3k - 1)} \sum^n_{i=1} \sum_{j \in \mathcal{N}_{i}^{k}}...scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html -
DummyClassifier — scikit-learn 1.6.0 documentation
([ - 1 , 1 , 1 , 1 ]) >>> y = np . array ([ 0 , 1 , 1 , 1 ]) >>>...dummy_clf . predict ( X ) array([1, 1, 1, 1]) >>> dummy_clf . score (...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html