{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4801","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4801/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4801/comments","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4801/events","html_url":"https://github.com/scikit-learn/scikit-learn/pull/4801","id":83792074,"number":4801,"title":"Discretization using Fayyad's MDLP stop criterion","user":{"login":"hlin117","id":1865885,"avatar_url":"https://avatars.githubusercontent.com/u/1865885?v=3","gravatar_id":"","url":"https://api.github.com/users/hlin117","html_url":"https://github.com/hlin117","followers_url":"https://api.github.com/users/hlin117/followers","following_url":"https://api.github.com/users/hlin117/following{/other_user}","gists_url":"https://api.github.com/users/hlin117/gists{/gist_id}","starred_url":"https://api.github.com/users/hlin117/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hlin117/subscriptions","organizations_url":"https://api.github.com/users/hlin117/orgs","repos_url":"https://api.github.com/users/hlin117/repos","events_url":"https://api.github.com/users/hlin117/events{/privacy}","received_events_url":"https://api.github.com/users/hlin117/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":26,"created_at":"2015-06-02T02:15:10Z","updated_at":"2015-06-19T00:10:52Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/4801","html_url":"https://github.com/scikit-learn/scikit-learn/pull/4801","diff_url":"https://github.com/scikit-learn/scikit-learn/pull/4801.diff","patch_url":"https://github.com/scikit-learn/scikit-learn/pull/4801.patch"},"body":"This pull request addresses #4468\r\n\r\nThis adds the feature of discretization using Fayyad's minimum description length principle (MDLP) stop criterion. The original paper describing the principle is <a href=\"http://ijcai.org/Past%20Proceedings/IJCAI-93-VOL2/PDF/022.pdf\">here</a>. Essentially, it splits the continuous attributes into intervals by minimizing the conditional entropy between the attribute in question and the class values.\r\n\r\nI demonstrate how to use this feature in <a href=\"https://gist.github.com/hlin117/dee443d98af5ac3413c5\">this gist</a>. I also show that it produces \"approximately\" the same output as the corresponding R package \"discretization\". I say \"approximately\" because there are indeed some rows where the output is not the same. However, I looked into this issue, and I am assuming that the R package actually has roundoff errors. Also note that this feature allows the users to specify which columns to discretize; the corresponding R package assumes each column is continuous."},"comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments/113323117","html_url":"https://github.com/scikit-learn/scikit-learn/pull/4801#issuecomment-113323117","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4801","id":113323117,"user":{"login":"ptully","id":11786363,"avatar_url":"https://avatars.githubusercontent.com/u/11786363?v=3","gravatar_id":"","url":"https://api.github.com/users/ptully","html_url":"https://github.com/ptully","followers_url":"https://api.github.com/users/ptully/followers","following_url":"https://api.github.com/users/ptully/following{/other_user}","gists_url":"https://api.github.com/users/ptully/gists{/gist_id}","starred_url":"https://api.github.com/users/ptully/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ptully/subscriptions","organizations_url":"https://api.github.com/users/ptully/orgs","repos_url":"https://api.github.com/users/ptully/repos","events_url":"https://api.github.com/users/ptully/events{/privacy}","received_events_url":"https://api.github.com/users/ptully/received_events","type":"User","site_admin":false},"created_at":"2015-06-19T00:10:52Z","updated_at":"2015-06-19T00:10:52Z","body":"I understand your point about Random Forests, where something similar is performed. But please see this paper for more in depth discussion:\r\n"}}