{"action":"closed","issue":{"url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/304","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/304/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/304/comments","events_url":"https://api.github.com/repos/scikit-learn-contrib/imbalanced-learn/issues/304/events","html_url":"https://github.com/scikit-learn-contrib/imbalanced-learn/issues/304","id":246549826,"number":304,"title":"resampling multiplier","user":{"login":"lifengjin","id":10468599,"avatar_url":"https://avatars0.githubusercontent.com/u/10468599?v=4","gravatar_id":"","url":"https://api.github.com/users/lifengjin","html_url":"https://github.com/lifengjin","followers_url":"https://api.github.com/users/lifengjin/followers","following_url":"https://api.github.com/users/lifengjin/following{/other_user}","gists_url":"https://api.github.com/users/lifengjin/gists{/gist_id}","starred_url":"https://api.github.com/users/lifengjin/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/lifengjin/subscriptions","organizations_url":"https://api.github.com/users/lifengjin/orgs","repos_url":"https://api.github.com/users/lifengjin/repos","events_url":"https://api.github.com/users/lifengjin/events{/privacy}","received_events_url":"https://api.github.com/users/lifengjin/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2017-07-29T22:44:12Z","updated_at":"2017-07-31T05:12:59Z","closed_at":"2017-07-31T05:12:59Z","body":"Thanks for the great package!\r\n\r\nIn this paper: https://arxiv.org/pdf/1707.03905.pdf , the authors talk about selecting multiplier for minority classes, which I read as instead of say oversampling to match the number of instances of the majority class, just oversample to some fraction of the number of instances of the majority class. Is there an easy way to do this with the random oversampler?\r\n"}}
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