{"action":"created","comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments/90220079","pull_request_review_id":10734908,"id":90220079,"diff_hunk":"@@ -0,0 +1,229 @@\n+import numpy as np\n+\n+from sklearn.datasets import ValueDropper\n+from sklearn.datasets import make_classification, make_regression\n+from sklearn.utils.testing import assert_equal\n+from sklearn.utils.testing import assert_true\n+from sklearn.utils.testing import assert_almost_equal\n+from sklearn.utils.testing import assert_array_almost_equal\n+from sklearn.utils.testing import assert_raise_message\n+from sklearn.utils.testing import assert_raises_regexp\n+from sklearn.preprocessing import LabelEncoder\n+\n+\n+def test_value_dropper_mnar_clf():\n+    # Test drop probabilites when missing distribution is\n+    # given for classification problems\n+    n_samples, n_features = 1000, 5\n+    X, y = make_classification(n_samples=n_samples,\n+                               n_classes=4,\n+                               n_features=n_features,\n+                               n_informative=5,\n+                               n_redundant=0,\n+                               n_repeated=0,\n+                               random_state=0)\n+    le = LabelEncoder().fit(['a', 'z', 'b', 'j'])\n+    y_str = le.inverse_transform(y)\n+    y_int = y\n+\n+    for y in (y_int, y_str):\n+        classes = np.unique(y)\n+\n+        # Inplace dropping of values\n+\n+        # Samples from class 0 will have a drop-probability of 0.1\n+        vd = ValueDropper(missing_proba={classes[0]: 0.1},\n+                          missing_values=np.nan, random_state=0)\n+        X_dropped = vd.transform(X, y)\n+        missing_mask = np.isnan(X_dropped)\n+\n+        # Check the drop-probabilty for class 0\n+        assert_almost_equal(missing_mask[y == classes[0]].sum() /\n+                            float(np.sum(y == classes[0]) * n_features), 0.1,\n+                            decimal=2)\n+\n+        # All the missing values are from y == 0\n+        assert_almost_equal(\n+            np.isnan(X_dropped[y == classes[0]]).ravel().sum() /\n+            float(np.sum(y == classes[0]) * n_features), 0.1, decimal=2)\n+\n+        # and no missing values from y != 0\n+        assert_equal(missing_mask[y != classes[0]].ravel().sum(), 0)\n+\n+        # Samples from class 1 will have a drop probabilty of 0.5\n+        # but spread unevenly across features as given by the\n+        # list of probabilities\n+        # And samples from class 0 will have a drop-probabilities as specified\n+        # by a list of drop-probabilites for each feature\n+        missing_proba = {classes[0]: [0.1, 0.2, 0.2, 0, 0],\n+                         classes[1]: 0.5}\n+        vd = ValueDropper(missing_proba=missing_proba,\n+                          missing_values=np.nan, random_state=0)\n+        X_dropped = vd.transform(X, y)\n+\n+        missing_mask = np.isnan(X_dropped)\n+        # Check that there are no missing values when y != {0 or 1}\n+        assert_equal(missing_mask[(y == classes[2])].ravel().sum(), 0)\n+        assert_equal(missing_mask[(y == classes[3])].ravel().sum(), 0)\n+\n+        # Check that the drop probabilites for samples of class 1 is 0.5\n+        # across all features\n+        assert_array_almost_equal(\n+            missing_mask[y == classes[1]].sum(axis=0) /\n+            float(np.sum(y == classes[1])), [0.5] * n_features, decimal=2)\n+\n+        # Check that the drop probabilites when class == 0  are as given by","path":"sklearn/datasets/tests/test_value_dropper.py","position":75,"original_position":75,"commit_id":"ca3b2e6fdb9296096f9306b5f66c9aa255665292","original_commit_id":"ca3b2e6fdb9296096f9306b5f66c9aa255665292","user":{"login":"TomDLT","id":11065596,"avatar_url":"https://avatars.githubusercontent.com/u/11065596?v=3","gravatar_id":"","url":"https://api.github.com/users/TomDLT","html_url":"https://github.com/TomDLT","followers_url":"https://api.github.com/users/TomDLT/followers","following_url":"https://api.github.com/users/TomDLT/following{/other_user}","gists_url":"https://api.github.com/users/TomDLT/gists{/gist_id}","starred_url":"https://api.github.com/users/TomDLT/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/TomDLT/subscriptions","organizations_url":"https://api.github.com/users/TomDLT/orgs","repos_url":"https://api.github.com/users/TomDLT/repos","events_url":"https://api.github.com/users/TomDLT/events{/privacy}","received_events_url":"https://api.github.com/users/TomDLT/received_events","type":"User","site_admin":false},"body":"double space","created_at":"2016-11-30T12:07:48Z","updated_at":"2016-11-30T12:13:26Z","html_url":"https://github.com/scikit-learn/scikit-learn/pull/7084#discussion_r90220079","pull_request_url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084","_links":{"self":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments/90220079"},"html":{"href":"https://github.com/scikit-learn/scikit-learn/pull/7084#discussion_r90220079"},"pull_request":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084"}}},"pull_request":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084","id":78865546,"html_url":"https://github.com/scikit-learn/scikit-learn/pull/7084","diff_url":"https://github.com/scikit-learn/scikit-learn/pull/7084.diff","patch_url":"https://github.com/scikit-learn/scikit-learn/pull/7084.patch","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/7084","number":7084,"state":"open","locked":false,"title":"[MRG] ENH add a ValueDropper to artificially insert missing values (NMAR or MCAR) to the dataset","user":{"login":"raghavrv","id":9487348,"avatar_url":"https://avatars.githubusercontent.com/u/9487348?v=3","gravatar_id":"","url":"https://api.github.com/users/raghavrv","html_url":"https://github.com/raghavrv","followers_url":"https://api.github.com/users/raghavrv/followers","following_url":"https://api.github.com/users/raghavrv/following{/other_user}","gists_url":"https://api.github.com/users/raghavrv/gists{/gist_id}","starred_url":"https://api.github.com/users/raghavrv/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/raghavrv/subscriptions","organizations_url":"https://api.github.com/users/raghavrv/orgs","repos_url":"https://api.github.com/users/raghavrv/repos","events_url":"https://api.github.com/users/raghavrv/events{/privacy}","received_events_url":"https://api.github.com/users/raghavrv/received_events","type":"User","site_admin":false},"body":"Fixes #6284 \r\n\r\n`ValueDropper` transformer class that has a `missing_distribution` attribute.\r\n\r\nThis can be:\r\n* a float for MCAR missingness specifying the rate of missing values, \r\n* a 1D array of probabilities for each feature (MCAR again)\r\n* For NMAR, a dict (of float / 1D array of probabilities for each feature) mapping labels to required distribution of missing values for samples belonging to that label.\r\n\r\nRefer [this example](https://github.com/scikit-learn/scikit-learn/pull/7084/files#diff-d2bd6608c5ae31fd62b233be32095553) for a better idea.\r\n\r\n- [x] `ValueDropper` to introduce missing values.\r\n- [x] Simplify and cleanup.\r\n- [x] Add example.\r\n- [x] Tests/doc\r\n\r\nI'd add an example for #5974 which will use this function to compare the missing value handling strategy for MCAR/MNAR missingness. \r\n\r\n@agramfort @GaelVaroquaux @amueller @jnothman @glouppe @MechCoder \r\n","created_at":"2016-07-26T14:49:38Z","updated_at":"2016-11-30T12:13:26Z","closed_at":null,"merged_at":null,"merge_commit_sha":"789a6fcf60cced2a342f9cb87f0c1e08645abbb7","assignee":{"login":"raghavrv","id":9487348,"avatar_url":"https://avatars.githubusercontent.com/u/9487348?v=3","gravatar_id":"","url":"https://api.github.com/users/raghavrv","html_url":"https://github.com/raghavrv","followers_url":"https://api.github.com/users/raghavrv/followers","following_url":"https://api.github.com/users/raghavrv/following{/other_user}","gists_url":"https://api.github.com/users/raghavrv/gists{/gist_id}","starred_url":"https://api.github.com/users/raghavrv/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/raghavrv/subscriptions","organizations_url":"https://api.github.com/users/raghavrv/orgs","repos_url":"https://api.github.com/users/raghavrv/repos","events_url":"https://api.github.com/users/raghavrv/events{/privacy}","received_events_url":"https://api.github.com/users/raghavrv/received_events","type":"User","site_admin":false},"assignees":[{"login":"raghavrv","id":9487348,"avatar_url":"https://avatars.githubusercontent.com/u/9487348?v=3","gravatar_id":"","url":"https://api.github.com/users/raghavrv","html_url":"https://github.com/raghavrv","followers_url":"https://api.github.com/users/raghavrv/followers","following_url":"https://api.github.com/users/raghavrv/following{/other_user}","gists_url":"https://api.github.com/users/raghavrv/gists{/gist_id}","starred_url":"https://api.github.com/users/raghavrv/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/raghavrv/subscriptions","organizations_url":"https://api.github.com/users/raghavrv/orgs","repos_url":"https://api.github.com/users/raghavrv/repos","events_url":"https://api.github.com/users/raghavrv/events{/privacy}","received_events_url":"https://api.github.com/users/raghavrv/received_events","type":"User","site_admin":false}],"milestone":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/milestones/21","html_url":"https://github.com/scikit-learn/scikit-learn/milestones/0.19","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/milestones/21/labels","id":1970916,"number":21,"title":"0.19","description":"","creator":{"login":"amueller","id":449558,"avatar_url":"https://avatars.githubusercontent.com/u/449558?v=3","gravatar_id":"","url":"https://api.github.com/users/amueller","html_url":"https://github.com/amueller","followers_url":"https://api.github.com/users/amueller/followers","following_url":"https://api.github.com/users/amueller/following{/other_user}","gists_url":"https://api.github.com/users/amueller/gists{/gist_id}","starred_url":"https://api.github.com/users/amueller/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/amueller/subscriptions","organizations_url":"https://api.github.com/users/amueller/orgs","repos_url":"https://api.github.com/users/amueller/repos","events_url":"https://api.github.com/users/amueller/events{/privacy}","received_events_url":"https://api.github.com/users/amueller/received_events","type":"User","site_admin":false},"open_issues":176,"closed_issues":39,"state":"open","created_at":"2016-08-29T22:34:33Z","updated_at":"2016-11-30T01:00:50Z","due_on":"2016-12-31T00:00:00Z","closed_at":null},"commits_url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084/commits","review_comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084/comments","review_comment_url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments{/number}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/7084/comments","statuses_url":"https://api.github.com/repos/scikit-learn/scikit-learn/statuses/ca3b2e6fdb9296096f9306b5f66c9aa255665292","head":{"label":"raghavrv:value_dropper","ref":"value_dropper","sha":"ca3b2e6fdb9296096f9306b5f66c9aa255665292","user":{"login":"raghavrv","id":9487348,"avatar_url":"https://avatars.githubusercontent.com/u/9487348?v=3","gravatar_id":"","url":"https://api.github.com/users/raghavrv","html_url":"https://github.com/raghavrv","followers_url":"https://api.github.com/users/raghavrv/followers","following_url":"https://api.github.com/users/raghavrv/following{/other_user}","gists_url":"https://api.github.com/users/raghavrv/gists{/gist_id}","starred_url":"https://api.github.com/users/raghavrv/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/raghavrv/subscriptions","organizations_url":"https://api.github.com/users/raghavrv/orgs","repos_url":"https://api.github.com/users/raghavrv/repos","events_url":"https://api.github.com/users/raghavrv/events{/privacy}","received_events_url":"https://api.github.com/users/raghavrv/received_events","type":"User","site_admin":false},"repo":{"id":26038110,"name":"scikit-learn","full_name":"raghavrv/scikit-learn","owner":{"login":"raghavrv","id":9487348,"avatar_url":"https://avatars.githubusercontent.com/u/9487348?v=3","gravatar_id":"","url":"https://api.github.com/users/raghavrv","html_url":"https://github.com/raghavrv","followers_url":"https://api.github.com/users/raghavrv/followers","following_url":"https://api.github.com/users/raghavrv/following{/other_user}","gists_url":"https://api.github.com/users/raghavrv/gists{/gist_id}","starred_url":"https://api.github.com/users/raghavrv/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/raghavrv/subscriptions","organizations_url":"https://api.github.com/users/raghavrv/orgs","repos_url":"https://api.github.com/users/raghavrv/repos","events_url":"https://api.github.com/users/raghavrv/events{/privacy}","received_events_url":"https://api.github.com/users/raghavrv/received_events","type":"User","site_admin":false},"private":false,"html_url":"https://github.com/raghavrv/scikit-learn","description":"scikit-learn: machine learning in Python","fork":true,"url":"https://api.github.com/repos/raghavrv/scikit-learn","forks_url":"https://api.github.com/repos/raghavrv/scikit-learn/forks","keys_url":"https://api.github.com/repos/raghavrv/scikit-learn/keys{/key_id}","collaborators_url":"https://api.github.com/repos/raghavrv/scikit-learn/collaborators{/collaborator}","teams_url":"https://api.github.com/repos/raghavrv/scikit-learn/teams","hooks_url":"https://api.github.com/repos/raghavrv/scikit-learn/hooks","issue_events_url":"https://api.github.com/repos/raghavrv/scikit-learn/issues/events{/number}","events_url":"https://api.github.com/repos/raghavrv/scikit-learn/events","assignees_url":"https://api.github.com/repos/raghavrv/scikit-learn/assignees{/user}","branches_url":"https://api.github.com/repos/raghavrv/scikit-learn/branches{/branch}","tags_url":"https://api.github.com/repos/raghavrv/scikit-learn/tags","blobs_url":"https://api.github.com/repos/raghavrv/scikit-learn/git/blobs{/sha}","git_tags_url":"https://api.github.com/repos/raghavrv/scikit-learn/git/tags{/sha}","git_refs_url":"https://api.github.com/repos/raghavrv/scikit-learn/git/refs{/sha}","trees_url":"https://api.github.com/repos/raghavrv/scikit-learn/git/trees{/sha}","statuses_url":"https://api.github.com/repos/raghavrv/scikit-learn/statuses/{sha}","languages_url":"https://api.github.com/repos/raghavrv/scikit-learn/languages","stargazers_url":"https://api.github.com/repos/raghavrv/scikit-learn/stargazers","contributors_url":"https://api.github.com/repos/raghavrv/scikit-learn/contributors","subscribers_url":"https://api.github.com/repos/raghavrv/scikit-learn/subscribers","subscription_url":"https://api.github.com/repos/raghavrv/scikit-learn/subscription","commits_url":"https://api.github.com/repos/raghavrv/scikit-learn/commits{/sha}","git_commits_url":"https://api.github.com/repos/raghavrv/scikit-learn/git/commits{/sha}","comments_url":"https://api.github.com/repos/raghavrv/scikit-learn/comments{/number}","issue_comment_url":"https://api.github.com/repos/raghavrv/scikit-learn/issues/comments{/number}","contents_url":"https://api.github.com/repos/raghavrv/scikit-learn/contents/{+path}","compare_url":"https://api.github.com/repos/raghavrv/scikit-learn/compare/{base}...{head}","merges_url":"https://api.github.com/repos/raghavrv/scikit-learn/merges","archive_url":"https://api.github.com/repos/raghavrv/scikit-learn/{archive_format}{/ref}","downloads_url":"https://api.github.com/repos/raghavrv/scikit-learn/downloads","issues_url":"https://api.github.com/repos/raghavrv/scikit-learn/issues{/number}","pulls_url":"https://api.github.com/repos/raghavrv/scikit-learn/pulls{/number}","milestones_url":"https://api.github.com/repos/raghavrv/scikit-learn/milestones{/number}","notifications_url":"https://api.github.com/repos/raghavrv/scikit-learn/notifications{?since,all,participating}","labels_url":"https://api.github.com/repos/raghavrv/scikit-learn/labels{/name}","releases_url":"https://api.github.com/repos/raghavrv/scikit-learn/releases{/id}","deployments_url":"https://api.github.com/repos/raghavrv/scikit-learn/deployments","created_at":"2014-11-01T00:56:31Z","updated_at":"2016-04-27T18:29:41Z","pushed_at":"2016-11-29T21:18:37Z","git_url":"git://github.com/raghavrv/scikit-learn.git","ssh_url":"git@github.com:raghavrv/scikit-learn.git","clone_url":"https://github.com/raghavrv/scikit-learn.git","svn_url":"https://github.com/raghavrv/scikit-learn","homepage":"http://scikit-learn.org","size":94850,"stargazers_count":0,"watchers_count":0,"language":"Python","has_issues":false,"has_downloads":true,"has_wiki":true,"has_pages":true,"forks_count":1,"mirror_url":null,"open_issues_count":1,"forks":1,"open_issues":1,"watchers":0,"default_branch":"master"}},"base":{"label":"scikit-learn:master","ref":"master","sha":"3292f2d1b31cf6bb45b531e178ff6c71bf69c82e","user":{"login":"scikit-learn","id":365630,"avatar_url":"https://avatars.githubusercontent.com/u/365630?v=3","gravatar_id":"","url":"https://api.github.com/users/scikit-learn","html_url":"https://github.com/scikit-learn","followers_url":"https://api.github.com/users/scikit-learn/followers","following_url":"https://api.github.com/users/scikit-learn/following{/other_user}","gists_url":"https://api.github.com/users/scikit-learn/gists{/gist_id}","starred_url":"https://api.github.com/users/scikit-learn/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/scikit-learn/subscriptions","organizations_url":"https://api.github.com/users/scikit-learn/orgs","repos_url":"https://api.github.com/users/scikit-learn/repos","events_url":"https://api.github.com/users/scikit-learn/events{/privacy}","received_events_url":"https://api.github.com/users/scikit-learn/received_events","type":"Organization","site_admin":false},"repo":{"id":843222,"name":"scikit-learn","full_name":"scikit-learn/scikit-learn","owner":{"login":"scikit-learn","id":365630,"avatar_url":"https://avatars.githubusercontent.com/u/365630?v=3","gravatar_id":"","url":"https://api.github.com/users/scikit-learn","html_url":"https://github.com/scikit-learn","followers_url":"https://api.github.com/users/scikit-learn/followers","following_url":"https://api.github.com/users/scikit-learn/following{/other_user}","gists_url":"https://api.github.com/users/scikit-learn/gists{/gist_id}","starred_url":"https://api.github.com/users/scikit-learn/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/scikit-learn/subscriptions","organizations_url":"https://api.github.com/users/scikit-learn/orgs","repos_url":"https://api.github.com/users/scikit-learn/repos","events_url":"https://api.github.com/users/scikit-learn/events{/privacy}","received_events_url":"https://api.github.com/users/scikit-learn/received_events","type":"Organization","site_admin":false},"private":false,"html_url":"https://github.com/scikit-learn/scikit-learn","description":"scikit-learn: machine learning in Python","fork":false,"url":"https://api.github.com/repos/scikit-learn/scikit-learn","forks_url":"https://api.github.com/repos/scikit-learn/scikit-learn/forks","keys_url":"https://api.github.com/repos/scikit-learn/scikit-learn/keys{/key_id}","collaborators_url":"https://api.github.com/repos/scikit-learn/scikit-learn/collaborators{/collaborator}","teams_url":"https://api.github.com/repos/scikit-learn/scikit-learn/teams","hooks_url":"https://api.github.com/repos/scikit-learn/scikit-learn/hooks","issue_events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/events{/number}","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/events","assignees_url":"https://api.github.com/repos/scikit-learn/scikit-learn/assignees{/user}","branches_url":"https://api.github.com/repos/scikit-learn/scikit-learn/branches{/branch}","tags_url":"https://api.github.com/repos/scikit-learn/scikit-learn/tags","blobs_url":"https://api.github.com/repos/scikit-learn/scikit-learn/git/blobs{/sha}","git_tags_url":"https://api.github.com/repos/scikit-learn/scikit-learn/git/tags{/sha}","git_refs_url":"https://api.github.com/repos/scikit-learn/scikit-learn/git/refs{/sha}","trees_url":"https://api.github.com/repos/scikit-learn/scikit-learn/git/trees{/sha}","statuses_url":"https://api.github.com/repos/scikit-learn/scikit-learn/statuses/{sha}","languages_url":"https://api.github.com/repos/scikit-learn/scikit-learn/languages","stargazers_url":"https://api.github.com/repos/scikit-learn/scikit-learn/stargazers","contributors_url":"https://api.github.com/repos/scikit-learn/scikit-learn/contributors","subscribers_url":"https://api.github.com/repos/scikit-learn/scikit-learn/subscribers","subscription_url":"https://api.github.com/repos/scikit-learn/scikit-learn/subscription","commits_url":"https://api.github.com/repos/scikit-learn/scikit-learn/commits{/sha}","git_commits_url":"https://api.github.com/repos/scikit-learn/scikit-learn/git/commits{/sha}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/comments{/number}","issue_comment_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments{/number}","contents_url":"https://api.github.com/repos/scikit-learn/scikit-learn/contents/{+path}","compare_url":"https://api.github.com/repos/scikit-learn/scikit-learn/compare/{base}...{head}","merges_url":"https://api.github.com/repos/scikit-learn/scikit-learn/merges","archive_url":"https://api.github.com/repos/scikit-learn/scikit-learn/{archive_format}{/ref}","downloads_url":"https://api.github.com/repos/scikit-learn/scikit-learn/downloads","issues_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues{/number}","pulls_url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls{/number}","milestones_url":"https://api.github.com/repos/scikit-learn/scikit-learn/milestones{/number}","notifications_url":"https://api.github.com/repos/scikit-learn/scikit-learn/notifications{?since,all,participating}","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/labels{/name}","releases_url":"https://api.github.com/repos/scikit-learn/scikit-learn/releases{/id}","deployments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/deployments","created_at":"2010-08-17T09:43:38Z","updated_at":"2016-11-30T09:27:16Z","pushed_at":"2016-11-30T09:46:40Z","git_url":"git://github.com/scikit-learn/scikit-learn.git","ssh_url":"git@github.com:scikit-learn/scikit-learn.git","clone_url":"https://github.com/scikit-learn/scikit-learn.git","svn_url":"https://github.com/scikit-learn/scikit-learn","homepage":"http://scikit-learn.org","size":129330,"stargazers_count":15026,"watchers_count":15026,"language":"Python","has_issues":true,"has_downloads":true,"has_wiki":true,"has_pages":false,"forks_count":8485,"mirror_url":null,"open_issues_count":1126,"forks":8485,"open_issues":1126,"watchers":15026,"default_branch":"master"}},"_links":{"self":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084"},"html":{"href":"https://github.com/scikit-learn/scikit-learn/pull/7084"},"issue":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/7084"},"comments":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/7084/comments"},"review_comments":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084/comments"},"review_comment":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments{/number}"},"commits":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/7084/commits"},"statuses":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/statuses/ca3b2e6fdb9296096f9306b5f66c9aa255665292"}}}}
{"actor":{"display_login":"TomDLT"}}