{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6781","repository_url":"https://api.github.com/repos/scikit-learn/scikit-learn","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6781/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6781/comments","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6781/events","html_url":"https://github.com/scikit-learn/scikit-learn/pull/6781","id":154853129,"number":6781,"title":"ENH: Add boxcox transform to preprocess input data","user":{"login":"maniteja123","id":6291963,"avatar_url":"https://avatars.githubusercontent.com/u/6291963?v=3","gravatar_id":"","url":"https://api.github.com/users/maniteja123","html_url":"https://github.com/maniteja123","followers_url":"https://api.github.com/users/maniteja123/followers","following_url":"https://api.github.com/users/maniteja123/following{/other_user}","gists_url":"https://api.github.com/users/maniteja123/gists{/gist_id}","starred_url":"https://api.github.com/users/maniteja123/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/maniteja123/subscriptions","organizations_url":"https://api.github.com/users/maniteja123/orgs","repos_url":"https://api.github.com/users/maniteja123/repos","events_url":"https://api.github.com/users/maniteja123/events{/privacy}","received_events_url":"https://api.github.com/users/maniteja123/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/labels/Needs%20Review","name":"Needs Review","color":"f7c6c7"}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":27,"created_at":"2016-05-14T13:12:33Z","updated_at":"2016-10-14T15:04:31Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/6781","html_url":"https://github.com/scikit-learn/scikit-learn/pull/6781","diff_url":"https://github.com/scikit-learn/scikit-learn/pull/6781.diff","patch_url":"https://github.com/scikit-learn/scikit-learn/pull/6781.patch"},"body":"#### Reference Issue\r\nSee #6675 \r\n\r\n#### What does this implement/fix? Explain your changes.\r\nImplement boxcox transform. The current approach is apply univariate on each feature with lambda being evaluated for maximising the log likelihood\r\n\r\n#### Any other comments?\r\nThis is just my initial attempt and am not sure if it is supposed to be computed in this manner. The documentation and tests need to be made better but first wanted to ask if this the expected functionality. Please do give any suggestions on improving this. Thanks.\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments/253827238","html_url":"https://github.com/scikit-learn/scikit-learn/pull/6781#issuecomment-253827238","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6781","id":253827238,"user":{"login":"maniteja123","id":6291963,"avatar_url":"https://avatars.githubusercontent.com/u/6291963?v=3","gravatar_id":"","url":"https://api.github.com/users/maniteja123","html_url":"https://github.com/maniteja123","followers_url":"https://api.github.com/users/maniteja123/followers","following_url":"https://api.github.com/users/maniteja123/following{/other_user}","gists_url":"https://api.github.com/users/maniteja123/gists{/gist_id}","starred_url":"https://api.github.com/users/maniteja123/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/maniteja123/subscriptions","organizations_url":"https://api.github.com/users/maniteja123/orgs","repos_url":"https://api.github.com/users/maniteja123/repos","events_url":"https://api.github.com/users/maniteja123/events{/privacy}","received_events_url":"https://api.github.com/users/maniteja123/received_events","type":"User","site_admin":false},"created_at":"2016-10-14T15:04:31Z","updated_at":"2016-10-14T15:04:31Z","body":"Hi @amueller , I have attempted to correct the grammar in the docs and also the plot is now based on the synthetic dataset on lines of the test provided by @agramfort . this is the plot now. Please do let me know if this seems a better example and also any other changes need to be done. Thanks.\r\n\r\n![boxcox](https://cloud.githubusercontent.com/assets/6291963/19392251/99b05f84-924d-11e6-9621-75915ac393fa.PNG)\r\n"}}
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