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RidgeClassifier — scikit-learn 1.7.0 documentation
converts the target values into {-1, 1} and then treats the problem...sklearn.linear_model. RidgeClassifier ( alpha = 1.0 , * , fit_intercept = True ,...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html -
check_is_fitted — scikit-learn 1.6.1 documentation
fit ([[ 1 , 2 ], [ 1 , 3 ]], [ 1 , 0 ]) LogisticRegression()...scikit-learn.org/stable/modules/generated/sklearn.utils.validation.check_is_fitted.html -
QuadraticDiscriminantAnalysis — scikit-learn 1....
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
MeanShift — scikit-learn 1.7.0 documentation
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . labels_ array([1, 1, 1, 0, 0, 0]) >>> clustering ....scikit-learn.org/stable/modules/generated/sklearn.cluster.MeanShift.html -
EllipticEnvelope — scikit-learn 1.7.0 documenta...
n_features + 1) / 2 * n_samples . Range is (0, 1). contamination...>>> # predict returns 1 for an inlier and -1 for an outlier >>>...scikit-learn.org/stable/modules/generated/sklearn.covariance.EllipticEnvelope.html -
RFE — scikit-learn 1.7.0 documentation
ranking_ array([1, 1, 1, 1, 1, 6, 4, 3, 2, 5]) decision_function...float, default=1 If greater than or equal to 1, then step corresponds...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFE.html -
auc — scikit-learn 1.7.0 documentation
array ([ 1 , 1 , 2 , 2 ]) >>> y_score = np . array ([ 0.1 , 0.4...scikit-learn.org/stable/modules/generated/sklearn.metrics.auc.html -
KernelRidge — scikit-learn 1.7.0 documentation
alpha = 1.0 ) >>> krr . fit ( X , y ) KernelRidge(alpha=1.0) fit...sklearn.kernel_ridge. KernelRidge ( alpha = 1 , * , kernel = 'linear' , gamma...scikit-learn.org/stable/modules/generated/sklearn.kernel_ridge.KernelRidge.html -
BayesianGaussianMixture — scikit-learn 1.7.0 do...
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], [ 4 , 2 ], [...mixtures”. Bayesian analysis 1.1 Examples >>> import numpy as...scikit-learn.org/stable/modules/generated/sklearn.mixture.BayesianGaussianMixture.html -
GridSearchCV — scikit-learn 1.7.0 documentation
means 1 unless in a joblib.parallel_backend context. -1 means...0.70 … 4 ‘rbf’ 0.1 – 0.80 … 3 ‘rbf’ 0.2 – 0.93 … 1 will be represented...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html