{"action":"created","issue":{"url":"https://api.github.com/repos/mlr-org/mlr/issues/878","repository_url":"https://api.github.com/repos/mlr-org/mlr","labels_url":"https://api.github.com/repos/mlr-org/mlr/issues/878/labels{/name}","comments_url":"https://api.github.com/repos/mlr-org/mlr/issues/878/comments","events_url":"https://api.github.com/repos/mlr-org/mlr/issues/878/events","html_url":"https://github.com/mlr-org/mlr/issues/878","id":153608628,"number":878,"title":"How to customise feature selection? Add new filters, use aggregate values from bootstrapping","user":{"login":"andrewjohnlowe","id":7668512,"avatar_url":"https://avatars.githubusercontent.com/u/7668512?v=3","gravatar_id":"","url":"https://api.github.com/users/andrewjohnlowe","html_url":"https://github.com/andrewjohnlowe","followers_url":"https://api.github.com/users/andrewjohnlowe/followers","following_url":"https://api.github.com/users/andrewjohnlowe/following{/other_user}","gists_url":"https://api.github.com/users/andrewjohnlowe/gists{/gist_id}","starred_url":"https://api.github.com/users/andrewjohnlowe/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/andrewjohnlowe/subscriptions","organizations_url":"https://api.github.com/users/andrewjohnlowe/orgs","repos_url":"https://api.github.com/users/andrewjohnlowe/repos","events_url":"https://api.github.com/users/andrewjohnlowe/events{/privacy}","received_events_url":"https://api.github.com/users/andrewjohnlowe/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":2,"created_at":"2016-05-07T18:08:33Z","updated_at":"2016-05-09T11:58:44Z","closed_at":null,"body":"Hello! I have two questions:\r\n\r\n1. Is there a way to define my own filter-based feature selection? I'd like to use the filter methods in CORElearn. Is this possible? If so, how can I define and plug-in my own filter, or one from another package?\r\n\r\n2. From past experience, I know that several of the filter-based measures that I'm interested in produce unstable results on my data. I'd like to bootstrap these measures and use an aggregate value -- mean or median -- instead. For example, info gain on my data seems to volatile, but the mean or median of a few tens of values evaluated on bootstrapped resamplings is stable. Ideally, I'd like to do bootstrapped filter-based feature selection (perhaps with a filter from another package; see Q1 above) as a step before learning, but fused with a learner, as part of nested cross-validation. I'm wondering if there is something like:\r\n`lrn = makeFilterWrapper(learner = \"classif.fnn\", fw.method = \"information.gain\", fw.abs = 2, fw.boot = 100)`\r\nfor example. Is this possible? If so, how? (Would be nice to also access the SD or IQR of the measures too.)\r\n\r\nThanks!"},"comment":{"url":"https://api.github.com/repos/mlr-org/mlr/issues/comments/217845215","html_url":"https://github.com/mlr-org/mlr/issues/878#issuecomment-217845215","issue_url":"https://api.github.com/repos/mlr-org/mlr/issues/878","id":217845215,"user":{"login":"andrewjohnlowe","id":7668512,"avatar_url":"https://avatars.githubusercontent.com/u/7668512?v=3","gravatar_id":"","url":"https://api.github.com/users/andrewjohnlowe","html_url":"https://github.com/andrewjohnlowe","followers_url":"https://api.github.com/users/andrewjohnlowe/followers","following_url":"https://api.github.com/users/andrewjohnlowe/following{/other_user}","gists_url":"https://api.github.com/users/andrewjohnlowe/gists{/gist_id}","starred_url":"https://api.github.com/users/andrewjohnlowe/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/andrewjohnlowe/subscriptions","organizations_url":"https://api.github.com/users/andrewjohnlowe/orgs","repos_url":"https://api.github.com/users/andrewjohnlowe/repos","events_url":"https://api.github.com/users/andrewjohnlowe/events{/privacy}","received_events_url":"https://api.github.com/users/andrewjohnlowe/received_events","type":"User","site_admin":false},"created_at":"2016-05-09T11:58:43Z","updated_at":"2016-05-09T11:58:43Z","body":"Hi Julia, thanks!\r\n\r\nCan I use a similar recipe to fuse a custom filter method to a learner? If makeFilter creates a filter and registers it with (for example) the name \"ReliefFequalK\", can I fuse it with a learner in the same way as those from FSelector?\r\n\r\nAny ideas on how to use bootstrapped filter measures in a filter fused with a learner? (2nd question) This would be very useful in cases (like mine) in which the filter measures are unstable.\r\n\r\nWhat do you mean by a PR? Sorry, don't understand. Happy to help, though.\r\n\r\nMy main reason for preferring CORElearn over FSelector is that previously I've encountered problems that resulted in execution failures:\r\nhttps://github.com/larskotthoff/fselector/issues/4\r\nThis isn't an issue with FSelector, but rather with RWeka. I haven't had time to follow-up with it, and instead found that CORElearn provided what I needed.\r\n\r\nBest regards,\r\n\r\nAndrew."}}