{"action":"created","issue":{"url":"https://api.github.com/repos/apache/spark/issues/4906","labels_url":"https://api.github.com/repos/apache/spark/issues/4906/labels{/name}","comments_url":"https://api.github.com/repos/apache/spark/issues/4906/comments","events_url":"https://api.github.com/repos/apache/spark/issues/4906/events","html_url":"https://github.com/apache/spark/pull/4906","id":59923013,"number":4906,"title":"[SPARK-6025] [MLlib] Add helper method evaluateEachIteration to extract learning curve","user":{"login":"MechCoder","id":1867024,"avatar_url":"https://avatars.githubusercontent.com/u/1867024?v=3","gravatar_id":"","url":"https://api.github.com/users/MechCoder","html_url":"https://github.com/MechCoder","followers_url":"https://api.github.com/users/MechCoder/followers","following_url":"https://api.github.com/users/MechCoder/following{/other_user}","gists_url":"https://api.github.com/users/MechCoder/gists{/gist_id}","starred_url":"https://api.github.com/users/MechCoder/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/MechCoder/subscriptions","organizations_url":"https://api.github.com/users/MechCoder/orgs","repos_url":"https://api.github.com/users/MechCoder/repos","events_url":"https://api.github.com/users/MechCoder/events{/privacy}","received_events_url":"https://api.github.com/users/MechCoder/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":46,"created_at":"2015-03-05T09:01:27Z","updated_at":"2015-03-18T13:52:27Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/apache/spark/pulls/4906","html_url":"https://github.com/apache/spark/pull/4906","diff_url":"https://github.com/apache/spark/pull/4906.diff","patch_url":"https://github.com/apache/spark/pull/4906.patch"},"body":"Added evaluateEachIteration to allow the user to manually extract the error for each iteration of GradientBoosting. The internal optimisation can be dealt with later."},"comment":{"url":"https://api.github.com/repos/apache/spark/issues/comments/82982129","html_url":"https://github.com/apache/spark/pull/4906#issuecomment-82982129","issue_url":"https://api.github.com/repos/apache/spark/issues/4906","id":82982129,"user":{"login":"MechCoder","id":1867024,"avatar_url":"https://avatars.githubusercontent.com/u/1867024?v=3","gravatar_id":"","url":"https://api.github.com/users/MechCoder","html_url":"https://github.com/MechCoder","followers_url":"https://api.github.com/users/MechCoder/followers","following_url":"https://api.github.com/users/MechCoder/following{/other_user}","gists_url":"https://api.github.com/users/MechCoder/gists{/gist_id}","starred_url":"https://api.github.com/users/MechCoder/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/MechCoder/subscriptions","organizations_url":"https://api.github.com/users/MechCoder/orgs","repos_url":"https://api.github.com/users/MechCoder/repos","events_url":"https://api.github.com/users/MechCoder/events{/privacy}","received_events_url":"https://api.github.com/users/MechCoder/received_events","type":"User","site_admin":false},"created_at":"2015-03-18T13:52:27Z","updated_at":"2015-03-18T13:52:27Z","body":"@jkbradley I have a silly query that I cannot refrain from asking.\r\n\r\nIf a point is predicted correctly, then the contribution of log loss due to that point should be zero right?\r\nHowever, if we take the log loss function, log(1+exp(−2y * F(x))) , let us say that y is 1, and F(x) which is the predicted label is also 1, then it contributes log(1 + exp(-2)) ~ 0.126 to the loss.\r\n\r\nThe log loss that I am familiar with, i.e log(1 + exp(-y * w' * x)) (where w is the weight and x is the feature vector), the contribution to the log loss approaches zero as w * x approaches infinity.\r\n\r\nHowever here w * x is continuous as compared to F(x) which is discrete."}}