{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4180","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4180/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4180/comments","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4180/events","html_url":"https://github.com/scikit-learn/scikit-learn/issues/4180","id":55928859,"number":4180,"title":"L1 feature selection docs confusing","user":{"login":"amueller","id":449558,"avatar_url":"https://avatars.githubusercontent.com/u/449558?v=3","gravatar_id":"","url":"https://api.github.com/users/amueller","html_url":"https://github.com/amueller","followers_url":"https://api.github.com/users/amueller/followers","following_url":"https://api.github.com/users/amueller/following{/other_user}","gists_url":"https://api.github.com/users/amueller/gists{/gist_id}","starred_url":"https://api.github.com/users/amueller/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/amueller/subscriptions","organizations_url":"https://api.github.com/users/amueller/orgs","repos_url":"https://api.github.com/users/amueller/repos","events_url":"https://api.github.com/users/amueller/events{/privacy}","received_events_url":"https://api.github.com/users/amueller/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/labels/Documentation","name":"Documentation","color":"0b02e1"}],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":5,"created_at":"2015-01-29T17:19:29Z","updated_at":"2015-02-08T21:15:44Z","closed_at":null,"body":"Here: http://scikit-learn.org/dev/modules/feature_selection.html#selecting-non-zero-coefficients\r\nMentions \"selecting non-zero coefficients via transform\" in \"LinearSVC\", \"LogisticRegression\" and \"Lasso\". Lasso doesn't have a transform, the other two use the median coefficient for feature selection, not being nonzero."},"comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments/73432297","html_url":"https://github.com/scikit-learn/scikit-learn/issues/4180#issuecomment-73432297","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4180","id":73432297,"user":{"login":"agramfort","id":161052,"avatar_url":"https://avatars.githubusercontent.com/u/161052?v=3","gravatar_id":"","url":"https://api.github.com/users/agramfort","html_url":"https://github.com/agramfort","followers_url":"https://api.github.com/users/agramfort/followers","following_url":"https://api.github.com/users/agramfort/following{/other_user}","gists_url":"https://api.github.com/users/agramfort/gists{/gist_id}","starred_url":"https://api.github.com/users/agramfort/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/agramfort/subscriptions","organizations_url":"https://api.github.com/users/agramfort/orgs","repos_url":"https://api.github.com/users/agramfort/repos","events_url":"https://api.github.com/users/agramfort/events{/privacy}","received_events_url":"https://api.github.com/users/agramfort/received_events","type":"User","site_admin":false},"created_at":"2015-02-08T21:15:44Z","updated_at":"2015-02-08T21:15:44Z","body":"> Oh, I just saw that the default depends on the penalty. That should be documented. I think that is the most important fix, as currently the default behavior for penalty='l1` is plainly wrong.\n\nwhy wrong? it takes the features with non-zero coefs as expected\n\n> The default in Lasso and ElasticNet is currently the median strategy, as they have no penalty parameter, right?\n\nthere is no transform for Lasso and ElasticNet\n"}}