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SVC — scikit-learn 1.7.1 documentation
kernel {‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’, ‘precomputed’} or callable,...( * , C = 1.0 , kernel = 'rbf' , degree = 3 , gamma = 'scale'...scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html -
GaussianProcessClassifier — scikit-learn 1.7.1 ...
the GP. If None is passed, the kernel “1.0 * RBF(1.0)” is used...load_iris ( return_X_y = True ) >>> kernel = 1.0 * RBF ( 1.0 ) >>>...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessClassifier.html -
QuantileRegressor — scikit-learn 1.7.1 document...
intercept. solver {‘highs-ds’, ‘highs-ipm’, ‘highs’, ‘interior-point’,...<= reg . predict ( X )) np.float64(0.8) fit ( X , y , sample_weight...scikit-learn.org/stable/modules/generated/sklearn.linear_model.QuantileRegressor.html -
make_circles — scikit-learn 1.7.1 documentation
shape (100,) >>> list ( y [: 5 ]) [np.int64(1), np.int64(1), np.int64(1),...np.int64(1), np.int64(0), np.int64(0)] Gallery examples # Classifier...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_circles.html -
make_moons — scikit-learn 1.7.1 documentation
datasets. make_moons ( n_samples = 100 , * , shuffle = True , noise...tuple of shape (2,), dtype=int, default=100 If int, the total number...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html -
mean_tweedie_deviance — scikit-learn 1.7.1 docu...
= [ 2 , 0 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5 , 2. , 2. ] >>>...mean_tweedie_deviance ( y_true , y_pred , power = 1 ) 1.4260... Gallery examples...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_tweedie_deviance.html -
coverage_error — scikit-learn 1.7.1 documentation
[[ 1 , 0 , 0 ], [ 0 , 1 , 1 ]] >>> y_score = [[ 1 , 0 , 0 ],...References [ 1 ] Tsoumakas, G., Katakis, I., & Vlahavas, I. (2010). Mining...scikit-learn.org/stable/modules/generated/sklearn.metrics.coverage_error.html -
plot_classifier_comparison.py
= X[:, 0].min() - 0.5, X[:, 0].max() + 0.5 y_min, y_max = X[:,...X[:, 1].min() - 0.5, X[:, 1].max() + 0.5 # just plot the dataset...scikit-learn.org/stable/_downloads/2da0534ab0e0c8241033bcc2d912e419/plot_classifier_comparison.py -
BayesianGaussianMixture — scikit-learn 1.7.1 do...
is kept. init_params {‘kmeans’, ‘k-means++’, ‘random’, ‘random_from_data’},...n_components. covariance_type {‘full’, ‘tied’, ‘diag’, ‘spherical’}, default=’full’...scikit-learn.org/stable/modules/generated/sklearn.mixture.BayesianGaussianMixture.html -
MinMaxScaler — scikit-learn 1.7.1 documentation
transform ( data )) [[0. 0. ] [0.25 0.25] [0.5 0.5 ] [1. 1. ]] >>>...X_std = ( X - X . min ( axis = 0 )) / ( X . max ( axis = 0 ) - X ....scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html