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Why did you calculate precision and recall instead of giving a prediction whether it is an anomaly or not? #1

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xuzhang5788 opened this issue Nov 1, 2018 · 1 comment

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@xuzhang5788
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Thank you for your clear code.

You used X_clean to train AE, and then if the input is X_bad_filtered, your model should classify them as anomalies. I understood your code like this. However, I don't understand why you calculated precision, recall, and F1. If there is a new dataset, how to classify each data as an anomaly or not?

@Rachnog
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Rachnog commented Nov 20, 2018

Hi @xuzhang5788 , in my case, I had labeled control data for anomalies, so I could calculate precision and recall :)

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