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HuberRegressor — scikit-learn 1.5.0 documentation
Epsilon must be in the range [1, inf) . max_iter...is equal to alpha * ||w||^2 . Must be in the range [0, inf) . warm_start...scikit-learn.org/stable/modules/generated/sklearn.linear_model.HuberRegressor.html -
RANSACRegressor — scikit-learn 1.5.0 documentation
inlier_mask_ bool array of shape [n_samples] Boolean mask of inliers...LinearRegression is used, the user must provide a value. residual_threshold...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RANSACRegressor.html -
Glossary of Common Terms and API Elements — sci...
and must do so if it is transductive . A clusterer must implement:...attributes after fitting, and that we must be careful to make meta-estimators...scikit-learn.org/dev/glossary.html -
Spectral clustering for image segmentation — sc...
mask = mask ) Take a decreasing function...np . full ( mask . shape , - 1.0 ) label_im [ mask ] = labels...scikit-learn.org/stable/auto_examples/cluster/plot_segmentation_toy.html -
SGDClassifier — scikit-learn 1.5.0 documentation
Values must be in the range [0.0, inf) ....penalty is ‘elasticnet’. Values must be in the range [0.0, 1.0] ....scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html -
Demo of DBSCAN clustering algorithm — scikit-le...
class_member_mask = labels == k xy = X [ class_member_mask & core_samples_mask...X [ class_member_mask & ~ core_samples_mask ] plt . plot ( xy...scikit-learn.org/stable/auto_examples/cluster/plot_dbscan.html -
Slashdot: News for nerds, stuff that matters
particles and fumes into the masks worn by patients. It could be...Food and Drug Administration -- must be met first. The move by a...devices.slashdot.org -
Compressive sensing: tomography reconstruction ...
logical_and ( mask > mask . mean (), mask_outer ) return np...list ( w [ mask ]) camera_inds += list ( inds [ mask ] + i * l_x...scikit-learn.org/stable/auto_examples/applications/plot_tomography_l1_reconstruction.html -
Partial Dependence and Individual Conditional E...
y_train = X [ mask_training ], y [ mask_training ] X_test..., y_test = X [ ~ mask_training ], y [ ~ mask_training ] We can...scikit-learn.org/stable/auto_examples/inspection/plot_partial_dependence.html -
Post-tuning the decision threshold for cost-sen...
fraudulent_refuse = ( mask_true_positive . sum () * 50 ) + amount [ mask_true_positive...y_true , y_pred , amount ): mask_true_positive = ( y_true ==...scikit-learn.org/stable/auto_examples/model_selection/plot_cost_sensitive_learning.html