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estimate_bandwidth — scikit-learn 1.7.1 documen...
([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7 ], [ 3 , 5 ],...sklearn.cluster. estimate_bandwidth ( X , * , quantile = 0.3 , n_samples...scikit-learn.org/stable/modules/generated/sklearn.cluster.estimate_bandwidth.html -
f_classif — scikit-learn 1.7.1 documentation
array([2.21e+02, 7.02e-01, 1.70e+00, 9.31e-01, 5.41e+00, 3.25e-01,...array([7.14e-27, 4.04e-01, 1.96e-01, 3.37e-01, 2.21e-02, 5.70e-01,...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html -
LassoCV — scikit-learn 1.7.1 documentation
is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...sklearn.linear_model. LassoCV ( * , eps = 0.001 , n_alphas = 'deprecated' , alphas...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoCV.html -
IncrementalPCA — scikit-learn 1.7.1 documentation
Issue 1-3, pp. 125-141, May 2008. See https://www.cs.toronto.edu...Bishop, 12.2.1 p. 574 or http://www.miketipping.com/papers/met-mppca.pdf...scikit-learn.org/stable/modules/generated/sklearn.decomposition.IncrementalPCA.html -
CountVectorizer — scikit-learn 1.7.1 documentation
ngram_range=(1 , 1) , analyzer='word' , max_df=1.0 , min_df=1 , max_features=None...analyzer {‘word’, ‘char’, ‘char_wb’} or callable, default=’word’ Whether...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html -
FactorAnalysis — scikit-learn 1.7.1 documentation
, tol = 0.01 , copy = True , max_iter = 1000 , noise_variance_init...svd_method {‘lapack’, ‘randomized’}, default=’randomized’ Which SVD...scikit-learn.org/stable/modules/generated/sklearn.decomposition.FactorAnalysis.html -
faq.rst.txt
the project ---------- What is the project name (a lot of people...Implementation decisions ---------- Why is there no support for deep or reinforcement...scikit-learn.org/stable/_sources/faq.rst.txt -
NearestCentroid — scikit-learn 1.7.1 documentation
np . array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1...1 , 1 ], [ 2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 ,...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestCentroid.html -
MDS — scikit-learn 1.7.1 documentation
of 0 indicates “perfect” fit, 0.025 excellent, 0.05 good, 0.1...'warn' , max_iter = 300 , verbose = 0 , eps = 1e-06 , n_jobs = None...scikit-learn.org/stable/modules/generated/sklearn.manifold.MDS.html -
hamming_loss — scikit-learn 1.7.1 documentation
hamming_loss ( np . array ([[ 0 , 1 ], [ 1 , 1 ]]), np . zeros (( 2 ,...3(3), 1-13, July-September 2007. [ 2 ] Wikipedia entry on the Hamming...scikit-learn.org/stable/modules/generated/sklearn.metrics.hamming_loss.html