- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 631 - 640 of 4,571 for * (2.56 sec)
-
SVC — scikit-learn 1.7.2 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 -
RidgeCV — scikit-learn 1.7.2 documentation
linear_model. RidgeCV ( alphas = (0.1, 1.0, 10.0) , * , fit_intercept...array-like of shape (n_alphas,), default=(0.1, 1.0, 10.0) Array...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeCV.html -
QuantileTransformer — scikit-learn 1.7.2 docume...
generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features...normal ( loc = 0.5 , scale = 0.25 , size = ( 25 , 1 )), axis =...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.QuantileTransformer.html -
roc_curve — scikit-learn 1.7.2 documentation
, 0. , 0.5, 0.5, 1. ]) >>> tpr array([0. , 0.5, 0.5, 1. , 1....1. ]) >>> thresholds array([ inf, 0.8 , 0.4 , 0.35, 0.1 ]) Gallery...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_curve.html -
PrecisionRecallDisplay — scikit-learn 1.7.2 doc...
train_test_split ( X , y , ... random_state = 0 ) >>> clf = SVC ( random_state...precision , recall = recall ) >>> disp . plot () <...> >>> plt . show...scikit-learn.org/stable/modules/generated/sklearn.metrics.PrecisionRecallDisplay.html -
r2_score — scikit-learn 1.7.2 documentation
948... >>> y_true = [[ 0.5 , 1 ], [ - 1 , 1 ], [ 7 , - 6 ]] >>>...[ 2.5 , 0.0 , 2 , 8 ] >>> r2_score ( y_true , y_pred ) 0.948......scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
make_moons — scikit-learn 1.7.2 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 -
make_circles — scikit-learn 1.7.2 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 -
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 -
plot_classifier_comparison.zip
= 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/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip