{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6191","repository_url":"https://api.github.com/repos/scikit-learn/scikit-learn","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6191/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6191/comments","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6191/events","html_url":"https://github.com/scikit-learn/scikit-learn/issues/6191","id":127509869,"number":6191,"title":"preprocessing.label_binarize for 2 classes gives single vector","user":{"login":"Borda","id":6035284,"avatar_url":"https://avatars.githubusercontent.com/u/6035284?v=3","gravatar_id":"","url":"https://api.github.com/users/Borda","html_url":"https://github.com/Borda","followers_url":"https://api.github.com/users/Borda/followers","following_url":"https://api.github.com/users/Borda/following{/other_user}","gists_url":"https://api.github.com/users/Borda/gists{/gist_id}","starred_url":"https://api.github.com/users/Borda/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Borda/subscriptions","organizations_url":"https://api.github.com/users/Borda/orgs","repos_url":"https://api.github.com/users/Borda/repos","events_url":"https://api.github.com/users/Borda/events{/privacy}","received_events_url":"https://api.github.com/users/Borda/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":7,"created_at":"2016-01-19T18:35:34Z","updated_at":"2016-10-05T16:35:16Z","closed_at":null,"body":"While you want to compute recall-precision for sklearn classifiers you cannot use general pipeline containing preprocessing.label_binarize (http://scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html) because it crash on case of just 2 classes, even it is documented it should not happen especially you do not know apriory number of classes."},"comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments/251728137","html_url":"https://github.com/scikit-learn/scikit-learn/issues/6191#issuecomment-251728137","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6191","id":251728137,"user":{"login":"Borda","id":6035284,"avatar_url":"https://avatars.githubusercontent.com/u/6035284?v=3","gravatar_id":"","url":"https://api.github.com/users/Borda","html_url":"https://github.com/Borda","followers_url":"https://api.github.com/users/Borda/followers","following_url":"https://api.github.com/users/Borda/following{/other_user}","gists_url":"https://api.github.com/users/Borda/gists{/gist_id}","starred_url":"https://api.github.com/users/Borda/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Borda/subscriptions","organizations_url":"https://api.github.com/users/Borda/orgs","repos_url":"https://api.github.com/users/Borda/repos","events_url":"https://api.github.com/users/Borda/events{/privacy}","received_events_url":"https://api.github.com/users/Borda/received_events","type":"User","site_admin":false},"created_at":"2016-10-05T16:35:16Z","updated_at":"2016-10-05T16:35:16Z","body":"I see only description, no reasonable example\r\n```\r\nneg_label : int (default: 0)\r\n        Value with which negative labels must be encoded.\r\npos_label : int (default: 1)\r\n        Value with which positive labels must be encoded.\r\n```\r\nwhich doe not justify why neg_label < pos_label for me...\r\nWell, looking to the co I understand what it does :)"}}
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