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BaseEstimator — scikit-learn 1.7.2 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 -
FunctionTransformer — scikit-learn 1.7.2 docume...
then X will be converted to a 2-dimensional NumPy array or sparse...X = np . array ([[ 0 , 1 ], [ 2 , 3 ]]) >>> transformer . transform...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html -
News
2.2 Released 2017-06-30 Fess 11.2.1 Released 2017-06-15...2016-11-07 Fess 10.2.2 Released 2016-10-02 Fess 10.2.1 Released 2016-08-30...fess.codelibs.org/news.html -
KNeighborsRegressor — scikit-learn 1.7.2 docume...
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html -
NeighborhoodComponentsAnalysis — scikit-learn 1...
ize will be set to verbose - 2 . random_state int or numpy.RandomState,...~roweis/papers/ncanips.pdf [ 2 ] Wikipedia entry on Neighborhood...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NeighborhoodComponentsAnalysis.html -
OPTICS — scikit-learn 1.7.2 documentation
2 (1999): 49-60. [ 2 ] Schubert, Erich, Michael...>>> X = np . array ([[ 1 , 2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8...scikit-learn.org/stable/modules/generated/sklearn.cluster.OPTICS.html -
8.2. Real world datasets — scikit-learn 1.7.2 d...
2.2. The 20 newsgroups text dataset...Ctrl + K GitHub Choose version 8.2. Real world datasets # scikit-learn...scikit-learn.org/stable/datasets/real_world.html -
KBinsDiscretizer — scikit-learn 1.7.2 documenta...
[ 2., 2., 2., 1.], [ 2., 2., 2., 2.]]) Sometimes...>>> X = [[ - 2 , 1 , - 4 , - 1 ], ... [ - 1 , 2 , - 3 , - 0.5...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KBinsDiscretizer.html -
NearestNeighbors — scikit-learn 1.7.2 documenta...
2 , return_distance = False ) array([[2, 0]]...) >>>...array([[2]])) As you can see, it returns [[0.5]], and [[2]], which...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestNeighbors.html -
HistGradientBoostingClassifier — scikit-learn 1...
2: Added support for feature names....version 0.23. Changed in version 1.2: Accept dict of constraints with...scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html