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Kernel — scikit-learn 1.5.2 documentation
length_scale = 2.0 ) >>> X = np . array ([[ 1 , 2 ], [ 3 , 4 ]])..., X if Y is None else Y ) ** 2 ... def diag ( self , X ): ......scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Kernel.html -
PLSCanonical — scikit-learn 1.5.2 documentation
[ 2. , 2. , 2. ], [ 2. , 5. , 4. ]] >>> y =...= [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 , 12.3...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSCanonical.html -
BaseEstimator — scikit-learn 1.5.2 documentation
predict ( X ) array([2, 2, 2]) >>> estimator . set_params...param = 2 ) >>> estimator . get_params () {'param': 2} >>> X =...scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html -
AgglomerativeClustering — scikit-learn 1.5.2 do...
2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2 ], [ 4 , 4...AgglomerativeCluster ( n_clusters = 2 , * , metric = 'euclidean' , memory...scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html -
IncrementalPCA — scikit-learn 1.5.2 documentation
[ - 2 , - 1 ], [ - 3 , - 2 ], ... [ 1 , 1 ], [ 2 , 1 ], [...O(batch_size * n_features ** 2) , but only 2 * batch_size samples remain...scikit-learn.org/stable/modules/generated/sklearn.decomposition.IncrementalPCA.html -
LassoCV — scikit-learn 1.5.2 documentation
is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoCV.html -
FeatureHasher — scikit-learn 1.5.2 documentation
'cat' : 2 , 'elephant' : 4 },{ 'dog' : 2 , 'run' : 5 }]...0., 0., 0., 0., 0., 2.], [ 0., 0., 0., -2., -5., 0., 0., 0., 0.,...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
FeatureUnion — scikit-learn 1.5.2 documentation
n_components = 2 ))]) >>> X = [[ 0. , 1. , 3 ], [ 2. , 2. , 5 ]] >>>...parameters. Added in version 1.2. n_features_in_ int Number of...scikit-learn.org/stable/modules/generated/sklearn.pipeline.FeatureUnion.html -
OutputCodeClassifier — scikit-learn 1.5.2 docum...
Artificial Intelligence Research 2, 1995. [ 2 ] “The error coding method...n_features = 4 , ... n_informative = 2 , n_redundant = 0 , ... random_state...scikit-learn.org/stable/modules/generated/sklearn.multiclass.OutputCodeClassifier.html -
KNeighborsClassifier — scikit-learn 1.5.2 docum...
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which...'auto' , leaf_size = 30 , p = 2 , metric = 'minkowski' , metric_params...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html