15 lines
566 B
Plaintext
15 lines
566 B
Plaintext
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Learned from DMC: Crossvalidation is important
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Rarely found in Anomaly Detection, why?
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A bit more complicated (not all samples are equal), but no reason why not
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->So I implemented it into yano
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<l2st>
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folding only on normal data
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How to handle anomalies?
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If not folding them, cross-validation less useful
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if folding them, often rare anomalies even more rare
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->test set always 50\% anomalous
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->Also improves simple evaluation metrics (accuracy)
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</l2st>
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Do you know a reason why Cross Validation is not common in AD?
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Are there Problems with the way I fold my Anomalies?
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