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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 -
Steve Albini - Wikipedia
References [ edit ] ^ a b c Gardin, Russel (April 20, 2018)....Retrieved December 4, 2023 . ^ a b c d Thorn, Jesse (December 6, 2007)....en.wikipedia.org/wiki/Steve_Albini -
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 -
sklearn.naive_bayes.BernoulliNB — scikit-learn ...
References C.D. Manning, P. Raghavan and H....The input samples. Returns : C ndarray of shape (n_samples,)...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.BernoulliNB.html -
sklearn.naive_bayes.GaussianNB — scikit-learn 1...
Returns : C ndarray of shape (n_samples,)...The input samples. Returns : C ndarray of shape (n_samples, n_classes)...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html -
model_evaluation.rst.txt
math:: \frac{1}{c(c-1)}\sum_{j=1}^{c}\sum_{k > j}^c (\text{AUC}(j...math:: \frac{1}{c(c-1)}\sum_{j=1}^{c}\sum_{k > j}^c p(j \cup k)(...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
sklearn.linear_model.LogisticRegression — sciki...
C = 1.0 , fit_intercept = True ,...both dense and sparse input. Use C-ordered arrays or CSR matrices...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html -
sklearn.inspection.DecisionBoundaryDisplay — sc...
c = iris . target , edgecolor =...scatter ( X [:, 0 ], X [:, 1 ], c = iris . target , edgecolor =...scikit-learn.org/stable/modules/generated/sklearn.inspection.DecisionBoundaryDisplay.html