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RadiusNeighborsRegressor — scikit-learn 1...
() array([[1., 0., 1.], [0., 1., 0.], [1., 0., 1.]]) score (...], [ 1 ], [ 2 ], [ 3 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.neighbors.RadiusNeighborsRegressor.html -
matthews_corrcoef — scikit-learn 1.7.2 do...
= [ + 1 , + 1 , + 1 , - 1 ] >>> y_pred = [ + 1 , - 1...value between -1 and +1. A coefficient of +1 represents a perfect...scikit-learn.org/stable/modules/generated/sklearn.metrics.matthews_corrcoef.html -
scale — scikit-learn 1.7.2 documentation
independently array([[-1., 1., 1.], [ 1., -1., -1.]]) >>>...>>> X = [[ - 2 , 1 , 2 ], [ - 1 , 0 , 1 ]] >>> scale...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html -
dict_learning_online — scikit-learn 1.7.2...
1 ( U , V ) with || V_k || _2 = 1 for all 0 <=...heuristics. Added in version 1.1. return_code bool, default=True...scikit-learn.org/stable/modules/generated/sklearn.decomposition.dict_learning_online.html -
Binarizer — scikit-learn 1.7.2 documentation
( X ) array([[1., 0., 1.], [1., 0., 0.], [0., 1., 0.]]) fit (...= [[ 1. , - 1. , 2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , -...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Binarizer.html -
mean_shift — scikit-learn 1.7.2 documenta...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...6. ], [1.33, 0.66]]) >>> labels array([1, 1, 1, 0, 0,...scikit-learn.org/stable/modules/generated/sklearn.cluster.mean_shift.html -
set_config — scikit-learn 1.7.2 documenta...
Added in version 1.1. enable_cython_pairwise_dist...configuration setting. Added in version 1.1. array_api_dispatch bool, default=None...scikit-learn.org/stable/modules/generated/sklearn.set_config.html -
Lars — scikit-learn 1.7.2 documentation
[ 1 , 1 ]], [ - 1.1111 , 0 , - 1.1111 ]) Lars(n_nonzero_coefs=1)...n_nonzero_coefs = 1 ) >>> reg . fit ([[ - 1 , 1 ], [ 0 , 0...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lars.html -
LassoLars — scikit-learn 1.7.2 documentation
([[ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ]], [ - 1 , 0 , - 1 ]) LassoLars(alpha=0.01)...sklearn.linear_model. LassoLars ( alpha = 1.0 , * , fit_intercept = True ,...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLars.html -
randomized_svd — scikit-learn 1.7.2 docum...
approximation problem described in [1] (problem (1.5), p5). Refer to Wikipedia...n_iter=0 or 1 should even work fine in theory (see [1] page 9)....scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.randomized_svd.html