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Hotgym predictor, anomaly tests #675
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Commits on Sep 18, 2019
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Hotgym: use TM.anomaly with different modes
remove explicit AnomalyLikelihood
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Hotgym: use SDRClassifier, Predictor WIP
but Predictor learn() crashes in Release, however does not in Debug (-> hard to investigate)
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Commits on Sep 20, 2019
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Hotgym: debugged crash with Predictor
crash was on bad_alloc (memory allocation failed). Our encoding to labels (realToCategory_()) had undeflow which resulted in a huge UInt -> tried to allocate extremely large vector -> failed.
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Hotgym: fewer steps in Predictor, for faster runtime
the 4 different step-ahead predictions took a lot of time
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Hotgym: Predictor not learning, still zero
add assert to catch whether we learn something.
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Predictor: add reproducible test for large labels
this crashes the Predictor. Likely a stack-overflow,
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Predictor: use type StepsAheadT for steps_
limit to unsingned short (from UInt)
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Classifier: numCategories_ is size_t
to avoid overflow for large labels
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Commits on Nov 6, 2019
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fix bindings for setAnomalyMode
needed to specify the argument for the signiture to be correct
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Commits on Nov 7, 2019
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