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sklearn.svm.SVR — scikit-learn 1.4.2 documentation
C = 1.0 , epsilon = 0.1 , shrinking...free parameters in the model are C and epsilon. The implementation...scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html -
Supervised learning: predicting an output varia...
c_ [ .5 , 1 ] . T >>> y = [ .5 , 1 ] >>> test = np . c_ [...is set by the C parameter: a small value for C means the margin...scikit-learn.org/stable/tutorial/statistical_inference/supervised_learning.html -
sklearn.linear_model.HuberRegressor — scikit-le...
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 -
sklearn.svm.LinearSVC — scikit-learn 1.4.2 docu...
the parameter C of class i to class_weight[i]*C for SVC. If not...dual = 'warn' , tol = 0.0001 , C = 1.0 , multi_class = 'ovr' ,...scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html -
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 -
Model selection: choosing estimators and their ...
"c" , "c" , "c" , "c" , "c" ] >>> k_fold = KFold...True ) >>> svc = svm . SVC ( C = 1 , kernel = 'linear' ) >>>...scikit-learn.org/stable/tutorial/statistical_inference/model_selection.html -
sklearn.preprocessing.PolynomialFeatures — scik...
order {‘C’, ‘F’}, default=’C’ Order of output array...include_bias = True , order = 'C' ) [source] Generate polynomial...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html -
Release Highlights for scikit-learn 1.0 — sciki...
or with conda: conda install - c conda - forge scikit - learn Keyword...]], columns = [ "a" , "b" , "c" ]) scalar = StandardScaler ()...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html -
sklearn.decomposition.PCA — scikit-learn 1.4.2 ...
Recognition and Machine Learning” by C. Bishop, 12.2.1 p. 574 or htt...from: Tipping, M. E., and Bishop, C. M. (1999). “Probabilistic principal...scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html -
sklearn.svm.NuSVC — scikit-learn 1.4.2 document...
the parameter C of class i to class_weight[i]*C for SVC. If not...(n_classes,) Multipliers of parameter C of each class. Computed based...scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVC.html