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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 -
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 -
Robust linear model estimation using RANSAC — s...
) inlier_mask = ransac . inlier_mask_ outlier_mask = np . logical_not...scatter ( X [ inlier_mask ], y [ inlier_mask ], color = "yellowgreen"...scikit-learn.org/stable/auto_examples/linear_model/plot_ransac.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 -
sklearn.feature_extraction.image.grid_to_graph ...
mask = mask ) >>> print ( graph ) (0,...grid_to_graph ( n_x , n_y , n_z=1 , * , mask=None , return_as=<class 'sc...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.grid_to_graph.html -
Kernel Density Estimate of Species Distribution...
:: 5 ] land_mask = ( land_reference > - 9999...ravel ()]) . T xy = xy [ land_mask ] xy *= np . pi / 180.0 # Plot...scikit-learn.org/stable/auto_examples/neighbors/plot_species_kde.html -
Pixel importances with a parallel forest of tre...
mask = y < 5 X = X [ mask ] y = y [ mask ] A random...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances_faces.html -
sklearn.feature_extraction.image.img_to_graph —...
mask=None , return_as=<class 'sc...width, channel) 2D or 3D image. mask ndarray of shape (height, width)...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.img_to_graph.html -
Semi-supervised Classification on a Text Datase...
# select a mask of 20% of the train dataset y_mask = np . random...the non-masked subset to be unlabeled y_train [ ~ y_mask ] = -...scikit-learn.org/stable/auto_examples/semi_supervised/plot_semi_supervised_newsgroups.html -
Multiclass Receiver Operating Characteristic (R...
= a_mask [ ab_mask ] b_true = b_mask [ ab_mask ] idx_a = np ....label_b ab_mask = np . logical_or ( a_mask , b_mask ) a_true =...scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html