{"action":"created","issue":{"url":"https://api.github.com/repos/TinkaRombouts/Titanic-Forests/issues/1","labels_url":"https://api.github.com/repos/TinkaRombouts/Titanic-Forests/issues/1/labels{/name}","comments_url":"https://api.github.com/repos/TinkaRombouts/Titanic-Forests/issues/1/comments","events_url":"https://api.github.com/repos/TinkaRombouts/Titanic-Forests/issues/1/events","html_url":"https://github.com/TinkaRombouts/Titanic-Forests/issues/1","id":105255359,"number":1,"title":"Implement Random Forests using Python","user":{"login":"MacHeathz","id":13467977,"avatar_url":"https://avatars.githubusercontent.com/u/13467977?v=3","gravatar_id":"","url":"https://api.github.com/users/MacHeathz","html_url":"https://github.com/MacHeathz","followers_url":"https://api.github.com/users/MacHeathz/followers","following_url":"https://api.github.com/users/MacHeathz/following{/other_user}","gists_url":"https://api.github.com/users/MacHeathz/gists{/gist_id}","starred_url":"https://api.github.com/users/MacHeathz/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/MacHeathz/subscriptions","organizations_url":"https://api.github.com/users/MacHeathz/orgs","repos_url":"https://api.github.com/users/MacHeathz/repos","events_url":"https://api.github.com/users/MacHeathz/events{/privacy}","received_events_url":"https://api.github.com/users/MacHeathz/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":{"login":"TinkaRombouts","id":14148390,"avatar_url":"https://avatars.githubusercontent.com/u/14148390?v=3","gravatar_id":"","url":"https://api.github.com/users/TinkaRombouts","html_url":"https://github.com/TinkaRombouts","followers_url":"https://api.github.com/users/TinkaRombouts/followers","following_url":"https://api.github.com/users/TinkaRombouts/following{/other_user}","gists_url":"https://api.github.com/users/TinkaRombouts/gists{/gist_id}","starred_url":"https://api.github.com/users/TinkaRombouts/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/TinkaRombouts/subscriptions","organizations_url":"https://api.github.com/users/TinkaRombouts/orgs","repos_url":"https://api.github.com/users/TinkaRombouts/repos","events_url":"https://api.github.com/users/TinkaRombouts/events{/privacy}","received_events_url":"https://api.github.com/users/TinkaRombouts/received_events","type":"User","site_admin":false},"milestone":null,"comments":5,"created_at":"2015-09-07T18:33:05Z","updated_at":"2015-09-09T11:19:52Z","closed_at":null,"body":"Implement Random Forests using Python on Titanic Dataset"},"comment":{"url":"https://api.github.com/repos/TinkaRombouts/Titanic-Forests/issues/comments/138879535","html_url":"https://github.com/TinkaRombouts/Titanic-Forests/issues/1#issuecomment-138879535","issue_url":"https://api.github.com/repos/TinkaRombouts/Titanic-Forests/issues/1","id":138879535,"user":{"login":"MacHeathz","id":13467977,"avatar_url":"https://avatars.githubusercontent.com/u/13467977?v=3","gravatar_id":"","url":"https://api.github.com/users/MacHeathz","html_url":"https://github.com/MacHeathz","followers_url":"https://api.github.com/users/MacHeathz/followers","following_url":"https://api.github.com/users/MacHeathz/following{/other_user}","gists_url":"https://api.github.com/users/MacHeathz/gists{/gist_id}","starred_url":"https://api.github.com/users/MacHeathz/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/MacHeathz/subscriptions","organizations_url":"https://api.github.com/users/MacHeathz/orgs","repos_url":"https://api.github.com/users/MacHeathz/repos","events_url":"https://api.github.com/users/MacHeathz/events{/privacy}","received_events_url":"https://api.github.com/users/MacHeathz/received_events","type":"User","site_admin":false},"created_at":"2015-09-09T11:19:52Z","updated_at":"2015-09-09T11:19:52Z","body":"Ik moet zeggen dat een score van 0.874 toch best wel goed is. Dat is dan 37 procentpunt beter dan random. Je hebt meerdere methoden om de accuraatheid van je model uit te drukken, zoals Lift, Accuracy, Precision en Recall. Laten we die ook erbij pakken.\r\n\r\nOver je punt om het beter te begrijpen, R heeft ook gewoon een functie om een random forests model te trainen en te laten voorspellen. Maar misschien kunnen we het proberen in Octave te bouwen, om beter te snappen wat het nou doet? Iets meer lowlevel maar met dezelfde mogelijkheden.\r\n\r\nVoor de rest is R wel handig om inzicht te krijgen in de verschillende features en om daarvan grafieken te plotten, zoals ook importance of features. Ben ook benieuwd hoe die wordt bepaald. Ik heb al een paar dingen eruit gehaald, zoals titel, achternaam en deck. Heb jij nog ideeën? Kunnen we nog iets met de tekstcomponent van ticket oid?\r\n\r\nIk las op kaggle dat ze nu een test dataset erbij hebben gegeven, waarmee we kunnen testen, maar ze hebben ook nog een private test dataset achter de hand gehouden, waarmee ze als de competitie afgelopen is, over een paar maanden, de definitieve evaluatie van de modellen doen. Mensen die nu dus 100% scoren op de leaderboard zullen dan waarschijnlijk door de mand vallen."}}