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PLSRegression — scikit-learn 1.7.2 documentation
1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ],...intercept_ . Added in version 1.1. n_iter_ list of shape (n_components,)...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSRegression.html -
CountVectorizer — scikit-learn 1.7.2 documentation
[[0 1 1 1 0 0 1 0 1] [0 2 0 1 0 1 1 0 1] [1 0 0 1 1 0 1 1 1] [0...[[0 0 1 1 0 0 1 0 0 0 0 1 0] [0 1 0 1 0 1 0 1 0 0 1 0 0] [1 0 0...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html -
NearestNeighbors — scikit-learn 1.7.2 documenta...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) radius_neighbors...() array([[1., 0., 1.], [0., 1., 0.], [1., 0., 1.]]) set_params...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestNeighbors.html -
LabelBinarizer — scikit-learn 1.7.2 documentation
array([[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 1, 0]]) fit ( y ) [source]...array([1, 2, 4, 6]) >>> lb . transform ([ 1 , 6 ]) array([[1, 0,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelBinarizer.html -
KNeighborsClassifier — scikit-learn 1.7.2 docum...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...bors=1) >>> print ( neigh . kneighbors ([[ 1. , 1. , 1. ]]))...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html -
KNeighborsRegressor — scikit-learn 1.7.2 docume...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...bors=1) >>> print ( neigh . kneighbors ([[ 1. , 1. , 1. ]]))...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html -
OPTICS — scikit-learn 1.7.2 documentation
1, 1, 1]) For a more detailed example...min_samples int > 1 or float between 0 and 1, default=5 The number...scikit-learn.org/stable/modules/generated/sklearn.cluster.OPTICS.html -
ComplementNB — scikit-learn 1.7.2 documentation
Added in version 1.2. Changed in version 1.4: The default value...sklearn.naive_bayes. ComplementNB ( * , alpha = 1.0 , force_alpha = True , fit_prior...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.ComplementNB.html -
homogeneity_score — scikit-learn 1.7.2 document...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Non-perfect labelings...homogeneity_score ([ 0 , 0 , 1 , 1 ], [ 0 , 0 , 1 , 2 ])) 1.000000 >>> print...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_score.html -
SGDClassifier — scikit-learn 1.7.2 documentation
array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>>...(clip(decision_function(X), -1, 1) + 1) / 2. For other loss functions...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html