{"action":"opened","issue":{"url":"https://api.github.com/repos/vlfeat/matconvnet/issues/61","labels_url":"https://api.github.com/repos/vlfeat/matconvnet/issues/61/labels{/name}","comments_url":"https://api.github.com/repos/vlfeat/matconvnet/issues/61/comments","events_url":"https://api.github.com/repos/vlfeat/matconvnet/issues/61/events","html_url":"https://github.com/vlfeat/matconvnet/issues/61","id":56780460,"number":61,"title":"Binary classification with softmaxloss.","user":{"login":"luzhi","id":1143602,"avatar_url":"https://avatars.githubusercontent.com/u/1143602?v=3","gravatar_id":"","url":"https://api.github.com/users/luzhi","html_url":"https://github.com/luzhi","followers_url":"https://api.github.com/users/luzhi/followers","following_url":"https://api.github.com/users/luzhi/following{/other_user}","gists_url":"https://api.github.com/users/luzhi/gists{/gist_id}","starred_url":"https://api.github.com/users/luzhi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/luzhi/subscriptions","organizations_url":"https://api.github.com/users/luzhi/orgs","repos_url":"https://api.github.com/users/luzhi/repos","events_url":"https://api.github.com/users/luzhi/events{/privacy}","received_events_url":"https://api.github.com/users/luzhi/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2015-02-06T07:37:37Z","updated_at":"2015-02-06T07:37:37Z","closed_at":null,"body":"Hi,\r\n\r\nI'm doing a binary classification, where the two categories are mutual exclusive. The CNN network is based on the one used in ImageNet, where I changed the number of classes from 1000 to 2. But I have no idea how to determine the class category for a testing image, because the output of the **softmaxloss* layer is a number. Do I need to set up a threshold? The classes labels are set as 1 for positives and 2 for negatives. Thanks!"}}