{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4480","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4480/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4480/comments","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4480/events","html_url":"https://github.com/scikit-learn/scikit-learn/issues/4480","id":65696090,"number":4480,"title":"Documentation for 'normalize' in Ridge regression somewhat unclear","user":{"login":"signalseeker","id":112979,"avatar_url":"https://avatars.githubusercontent.com/u/112979?v=3","gravatar_id":"","url":"https://api.github.com/users/signalseeker","html_url":"https://github.com/signalseeker","followers_url":"https://api.github.com/users/signalseeker/followers","following_url":"https://api.github.com/users/signalseeker/following{/other_user}","gists_url":"https://api.github.com/users/signalseeker/gists{/gist_id}","starred_url":"https://api.github.com/users/signalseeker/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/signalseeker/subscriptions","organizations_url":"https://api.github.com/users/signalseeker/orgs","repos_url":"https://api.github.com/users/signalseeker/repos","events_url":"https://api.github.com/users/signalseeker/events{/privacy}","received_events_url":"https://api.github.com/users/signalseeker/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/labels/Documentation","name":"Documentation","color":"0b02e1"},{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/labels/Easy","name":"Easy","color":"02d7e1"}],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":5,"created_at":"2015-04-01T14:13:15Z","updated_at":"2015-04-02T09:48:12Z","closed_at":null,"body":"For linear models with regularization, the input variables should be standardized because the solution is not scale invariant. I noticed that in the ridge regression source code, the input variables are centered by mean subtraction but normalization by std deviation is a flag.\r\n\r\nMy questions are:\r\n1) Under what circumstances should normalized be set to True so that both centering and normalizing by std. dev are turned on?\r\n\r\n2) Does normalize=True affect prediction? When predicting from new X, should X be centered and normalized?\r\n\r\n3) Does normalizing have any affect on the range of alpha the regularization parameter? It would be nice to be able to restrict alpha to [0, 1].\r\n\r\nIt would be great if the documentation made this clear. Thanks."},"comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments/88851552","html_url":"https://github.com/scikit-learn/scikit-learn/issues/4480#issuecomment-88851552","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4480","id":88851552,"user":{"login":"daveudaimon","id":5487113,"avatar_url":"https://avatars.githubusercontent.com/u/5487113?v=3","gravatar_id":"","url":"https://api.github.com/users/daveudaimon","html_url":"https://github.com/daveudaimon","followers_url":"https://api.github.com/users/daveudaimon/followers","following_url":"https://api.github.com/users/daveudaimon/following{/other_user}","gists_url":"https://api.github.com/users/daveudaimon/gists{/gist_id}","starred_url":"https://api.github.com/users/daveudaimon/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/daveudaimon/subscriptions","organizations_url":"https://api.github.com/users/daveudaimon/orgs","repos_url":"https://api.github.com/users/daveudaimon/repos","events_url":"https://api.github.com/users/daveudaimon/events{/privacy}","received_events_url":"https://api.github.com/users/daveudaimon/received_events","type":"User","site_admin":false},"created_at":"2015-04-02T09:48:12Z","updated_at":"2015-04-02T09:48:12Z","body":"It's perfectly clear to me: centering is always done, normalization is optional:\r\n\r\n    Parameters\r\n    ----------\r\n    normalize : boolean, optional, default False\r\n        If True, the regressors X will be normalized before regression."}}