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ValidationCurveDisplay — scikit-learn 1.7.0 doc...
param_range = "C" , np . logspace ( - 8 , 3 , 10...>>> param_name , param_range = "C" , np . logspace ( - 8 , 3 , 10...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ValidationCurveDisplay.html -
OrdinalEncoder — scikit-learn 1.7.0 documentation
(c.f. bpo-43475 ). Examples Given...into a single category, “b” and “c” are their own categories, unknown...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html -
3.2. Tuning the hyper-parameters of an estimato...
Typical examples include C , kernel and gamma for Support...param_grid : param_grid = [ { 'C' : [ 1 , 10 , 100 , 1000 ], 'kernel'...scikit-learn.org/stable/modules/grid_search.html -
SplineTransformer — scikit-learn 1.7.0 document...
order {‘C’, ‘F’}, default=’C’ Order of output array...include_bias = True , order = 'C' , sparse_output = False ) [source]...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.SplineTransformer.html -
HuberRegressor — scikit-learn 1.7.0 documentation
the samples where |(y - Xw - c) / sigma| < epsilon and the absolute...the samples where |(y - Xw - c) / sigma| > epsilon , where the...scikit-learn.org/stable/modules/generated/sklearn.linear_model.HuberRegressor.html -
auto_examples_jupyter.zip
c in enumerate(centers):\n ax2.scatter(c[0], c[1], marker=\"$%d$\"...RANDOM_SEED)\nprint(\"Class\", \"P(C)\", \"P(w0|C)\", \"P(w1|C)\", sep=\"\\t\")\nfor...scikit-learn.org/stable/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip -
3.1. Cross-validation: evaluating estimator per...
"c" , "c" , "c" , "d" , "d" , "d" ] >>>..."a" , "b" , "b" , "b" , "c" , "c" , "c" , "a" ] >>> groups = [...scikit-learn.org/stable/modules/cross_validation.html -
decomposition.rst.txt
C. Sorensen, and C. Yang, (1998) .. _LSA:....org/Boutsidis_PRE_08.pdf>`_ C. Boutsidis, E. Gallopoulos, 2008...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
preprocessing.rst.txt
"b" and "c" are their own categories, unknown...... [["a"] * 5 + ["b"] * 20 + ["c"] * 10 + ["d"] * 3 + [np.nan]],...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
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