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Non-negative least squares — scikit-learn 1.7.1...
plot ([ low , high ], [ low , high ], ls = "--" , c = ".3" , alpha...coefficients" , fontweight = "bold" ) Text(55.847222222222214, 0.5, 'NNLS...scikit-learn.org/stable/auto_examples/linear_model/plot_nnls.html -
SVM Tie Breaking Example — scikit-learn 1.7.1 d...
classes = [( 0 , 1 ), ( 0 , 2 ), ( 1 , 2 )] line = np . linspace (...( X [:, 1 ] . min () - 5 , X [:, 1 ] . max () + 5 ) ax . imshow...scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html -
PowerTransformer — scikit-learn 1.7.1 documenta...
[[-1.316 -0.707] [ 0.209 -0.707] [ 1.106 1.414]] fit ( X , y =...generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html -
ShuffleSplit — scikit-learn 1.7.1 documentation
split ( X )): ... print ( f "Fold { i } :" ) ... print ( f " Train:...enumerate ( rs . split ( X )): ... print ( f "Fold { i } :" ) ... print...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
check_estimator — scikit-learn 1.7.1 documentation
status ( one of "xfail" , "failed" , "skipped" , "passed" ), "expected_to_fail"...Literal [ "xfail" , "failed" , "skipped" , "passed" ], expected_to_fail...scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.check_estimator.html -
make_column_selector — scikit-learn 1.7.1 docum...
50755672, 1. , 0. , 0. ], [-0.30151134, 0. , 1. , 0. ], [ 0.90453403,...fit_transform ( X ) array([[ 0.90453403, 1. , 0. , 0. ], [-1.50755672,...scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_selector.html -
export_graphviz — scikit-learn 1.7.1 documentation
class name. label {‘all’, ‘root’, ‘none’}, default=’all’ Whether...names. If None, generic names will be used (“x[0]”, “x[1]”, …)....scikit-learn.org/stable/modules/generated/sklearn.tree.export_graphviz.html -
compute_class_weight — scikit-learn 1.7.1 docum...
y = [ 1 , 1 , 1 , 1 , 0 , 0 ] >>> compute_class_weight ( class_weight...class_weight = "balanced" , classes = np . unique ( y ), y = y ) array([1.5...scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_class_weight.html -
laplacian_kernel — scikit-learn 1.7.1 documenta...
1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>> laplacian_kernel...laplacian_kernel ( X , Y ) array([[0.71, 0.51], [0.51, 0.71]]) On this...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.laplacian_kernel.html -
load_svmlight_file — scikit-learn 1.7.1 documen...
each (see https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/data...zero_based='auto' , query_id=False , offset=0 , length=-1 ) [source] # Load datasets...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_svmlight_file.html