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Plot the support vectors in LinearSVC — scikit-...
linestyles = [ "--" , "-" , "--" ], ) plt . scatter ( support_vectors...figsize = ( 10 , 5 )) for i , C in enumerate ([ 1 , 100 ]): # "hinge"...scikit-learn.org/stable/auto_examples/svm/plot_linearsvc_support_vectors.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 -
ElasticNet — scikit-learn 1.7.1 documentation
linear_model. ElasticNet ( alpha = 1.0 , * , l1_ratio = 0.5 , fit_intercept...n_samples ) * || y - Xw ||^ 2_2 + alpha * l1_ratio * || w || _1 + 0.5...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html -
MultiTaskLassoCV — scikit-learn 1.7.1 documenta...
MultiTaskLasso is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ Fro_2 + alpha...random_state = 0 ) . fit ( X , y ) >>> r2_score ( y , reg . predict ( X ))...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLassoCV.html -
IncrementalPCA — scikit-learn 1.7.1 documentation
Bishop, 12.2.1 p. 574 or http://www.miketipping.com/papers/met-mppca.pdf...Issue 1-3, pp. 125-141, May 2008. See https://www.cs.toronto.edu...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 -
LarsCV — scikit-learn 1.7.1 documentation
LarsCV ( cv = 5 ) . fit ( X , y ) >>> reg . score ( X , y ) 0.9996...,]) array([154.3996]) fit ( X , y , ** params ) [source] # Fit...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LarsCV.html -
decomposition.rst.txt
tion.py` .. _IncrementalPCA: Incremental PCA ---------- The :class:`PCA`...the SVD. .. figure:: ../auto_examples/decomposition/images/sphx...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
grid_search.rst.txt
[1, 10, 100, 1000], 'gamma': [0.001, 0.0001], 'kernel': ['rbf']},...= [ {'C': [1, 10, 100, 1000], 'kernel': ['linear']}, {'C': [1,...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
as_float_array — scikit-learn 1.7.1 documentation
as_float_array ( array ) array([0., 0., 1., 2., 2.]) On this page...= np . array ([ 0 , 0 , 1 , 2 , 2 ], dtype = np . int64 ) >>>...scikit-learn.org/stable/modules/generated/sklearn.utils.as_float_array.html