{"action":"created","issue":{"url":"https://api.github.com/repos/amueller/scipy-2016-sklearn/issues/81","repository_url":"https://api.github.com/repos/amueller/scipy-2016-sklearn","labels_url":"https://api.github.com/repos/amueller/scipy-2016-sklearn/issues/81/labels{/name}","comments_url":"https://api.github.com/repos/amueller/scipy-2016-sklearn/issues/81/comments","events_url":"https://api.github.com/repos/amueller/scipy-2016-sklearn/issues/81/events","html_url":"https://github.com/amueller/scipy-2016-sklearn/issues/81","id":186150805,"number":81,"title":"Refine the explanation for the sklearn metrics section","user":{"login":"rhiever","id":1719223,"avatar_url":"https://avatars.githubusercontent.com/u/1719223?v=3","gravatar_id":"","url":"https://api.github.com/users/rhiever","html_url":"https://github.com/rhiever","followers_url":"https://api.github.com/users/rhiever/followers","following_url":"https://api.github.com/users/rhiever/following{/other_user}","gists_url":"https://api.github.com/users/rhiever/gists{/gist_id}","starred_url":"https://api.github.com/users/rhiever/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/rhiever/subscriptions","organizations_url":"https://api.github.com/users/rhiever/orgs","repos_url":"https://api.github.com/users/rhiever/repos","events_url":"https://api.github.com/users/rhiever/events{/privacy}","received_events_url":"https://api.github.com/users/rhiever/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2016-10-30T17:46:06Z","updated_at":"2016-11-02T18:21:14Z","closed_at":null,"body":"Currently the sklearn metrics section discusses a whole bunch of metrics but doesn't seem to go into detail on why you would use one particular metric. One point I usually try to make about metrics is that the \"correct\" metric depends critically on your problem, e.g.,\n- if you're doing spam detection, maybe a FN isn't so bad, so you can use a metric that focuses on maximizing FP and TP\n- but if you're doing cancer detection, a FN is disastrous, so you would use a metric that focuses in minimizing FN (even at the expense of others)\n- etc.\n\nIMO it's a good idea to give students an intuition behind why we choose certain metrics in ML.\n"},"comment":{"url":"https://api.github.com/repos/amueller/scipy-2016-sklearn/issues/comments/257954556","html_url":"https://github.com/amueller/scipy-2016-sklearn/issues/81#issuecomment-257954556","issue_url":"https://api.github.com/repos/amueller/scipy-2016-sklearn/issues/81","id":257954556,"user":{"login":"rasbt","id":5618407,"avatar_url":"https://avatars.githubusercontent.com/u/5618407?v=3","gravatar_id":"","url":"https://api.github.com/users/rasbt","html_url":"https://github.com/rasbt","followers_url":"https://api.github.com/users/rasbt/followers","following_url":"https://api.github.com/users/rasbt/following{/other_user}","gists_url":"https://api.github.com/users/rasbt/gists{/gist_id}","starred_url":"https://api.github.com/users/rasbt/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/rasbt/subscriptions","organizations_url":"https://api.github.com/users/rasbt/orgs","repos_url":"https://api.github.com/users/rasbt/repos","events_url":"https://api.github.com/users/rasbt/events{/privacy}","received_events_url":"https://api.github.com/users/rasbt/received_events","type":"User","site_admin":false},"created_at":"2016-11-02T18:21:14Z","updated_at":"2016-11-02T18:21:14Z","body":"> if you're doing spam detection, maybe a FN isn't so bad, so you can use a metric that focuses on maximizing FP and TP\r\nbut if you're doing cancer detection, a FN is disastrous, so you would use a metric that focuses in minimizing FN (even at the expense of others)\r\netc.\r\n\r\nGreat point! I think we explained this verbally in the tutorial (or maybe it was a different talk?), but it would be great to add this to the notebooks!!"}}
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