{"action":"opened","number":4802,"pull_request":{"url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/pulls/4802","id":174902355,"html_url":"https://github.com/deeplearning4j/deeplearning4j/pull/4802","diff_url":"https://github.com/deeplearning4j/deeplearning4j/pull/4802.diff","patch_url":"https://github.com/deeplearning4j/deeplearning4j/pull/4802.patch","issue_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/4802","number":4802,"state":"open","locked":false,"title":"Evaluation: Properly handle no-arg binary metrics for binary case","user":{"login":"AlexDBlack","id":2360237,"avatar_url":"https://avatars0.githubusercontent.com/u/2360237?v=4","gravatar_id":"","url":"https://api.github.com/users/AlexDBlack","html_url":"https://github.com/AlexDBlack","followers_url":"https://api.github.com/users/AlexDBlack/followers","following_url":"https://api.github.com/users/AlexDBlack/following{/other_user}","gists_url":"https://api.github.com/users/AlexDBlack/gists{/gist_id}","starred_url":"https://api.github.com/users/AlexDBlack/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/AlexDBlack/subscriptions","organizations_url":"https://api.github.com/users/AlexDBlack/orgs","repos_url":"https://api.github.com/users/AlexDBlack/repos","events_url":"https://api.github.com/users/AlexDBlack/events{/privacy}","received_events_url":"https://api.github.com/users/AlexDBlack/received_events","type":"User","site_admin":false},"body":"Fixes: https://github.com/deeplearning4j/deeplearning4j/issues/4759\r\n\r\nPreviously: Evaluation.f1(), .precision(), .recall() etc returned the macro-averaged values for the non-binary case. Macro-averaging makes sense for the multi-class case, but not the binary case.\r\nThe no-arg methods (f1() etc) now report the binary metric that would be expected.\r\n\r\nJavadoc and stats() method now also make it clear exactly what is being reported for the binary vs. non-binary cases.\r\n\r\n```\r\nPredictions labeled as 0 classified by model as 0: 3 times\r\nPredictions labeled as 0 classified by model as 1: 1 times\r\nPredictions labeled as 1 classified by model as 0: 5 times\r\nPredictions labeled as 1 classified by model as 1: 7 times\r\n\r\n\r\n==========================Scores========================================\r\n # of classes:    2\r\n Accuracy:        0.6250\r\n Precision:       0.6250\r\n Recall:          0.6667\r\n F1 Score:        0.7000\r\nPrecision, recall & F1: reported for positive class (class 1 - \"1\") 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