{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/199","repository_url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn","labels_url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/199/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/199/comments","events_url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/199/events","html_url":"https://github.com/scikit-learn-contrib/imbalanced-learn/issues/199","id":196024722,"number":199,"title":"SMOTE oversampling providing samples full of -1 value","user":{"login":"ykacer","id":16710784,"avatar_url":"https://avatars.githubusercontent.com/u/16710784?v=3","gravatar_id":"","url":"https://api.github.com/users/ykacer","html_url":"https://github.com/ykacer","followers_url":"https://api.github.com/users/ykacer/followers","following_url":"https://api.github.com/users/ykacer/following{/other_user}","gists_url":"https://api.github.com/users/ykacer/gists{/gist_id}","starred_url":"https://api.github.com/users/ykacer/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ykacer/subscriptions","organizations_url":"https://api.github.com/users/ykacer/orgs","repos_url":"https://api.github.com/users/ykacer/repos","events_url":"https://api.github.com/users/ykacer/events{/privacy}","received_events_url":"https://api.github.com/users/ykacer/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2016-12-16T10:16:13Z","updated_at":"2016-12-16T10:37:09Z","closed_at":"2016-12-16T10:37:09Z","body":"Hi,\r\n\r\nI'm using` SMOTE` to over-sample my very imbalanced data (`ratio = 3000`). I'm using `SMOTE` with all default parameters and it provides a vector label of same size and full of -1. However, initials labels are positives. Is there something i missed? Is it an unexpected behavior or do I have to tune parameters? if so, which you think is the priority parameter?\r\nThanks for your help"},"comment":{"url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/comments/267565725","html_url":"https://github.com/scikit-learn-contrib/imbalanced-learn/issues/199#issuecomment-267565725","issue_url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/199","id":267565725,"user":{"login":"ykacer","id":16710784,"avatar_url":"https://avatars.githubusercontent.com/u/16710784?v=3","gravatar_id":"","url":"https://api.github.com/users/ykacer","html_url":"https://github.com/ykacer","followers_url":"https://api.github.com/users/ykacer/followers","following_url":"https://api.github.com/users/ykacer/following{/other_user}","gists_url":"https://api.github.com/users/ykacer/gists{/gist_id}","starred_url":"https://api.github.com/users/ykacer/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ykacer/subscriptions","organizations_url":"https://api.github.com/users/ykacer/orgs","repos_url":"https://api.github.com/users/ykacer/repos","events_url":"https://api.github.com/users/ykacer/events{/privacy}","received_events_url":"https://api.github.com/users/ykacer/received_events","type":"User","site_admin":false},"created_at":"2016-12-16T10:37:09Z","updated_at":"2016-12-16T10:37:09Z","body":"Got it! just a careless mistake."}}
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