[7.17][ML] Address the root cause for "actual equals typical equals zero" anomalies #2551
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…nomalies (#2270) We've had multiple issues reported in the past where we report high anomaly scores when the actual is the same as the typical and both are equal to zero. This has been exacerbated in the past because we've also had some instabilities in the modelling when we stop receiving data for a partition, which was an edge case when this could occur. In all problematic cases, the underlying reason is the if we know the data are non-negative we truncate the prediction when we report the typical value. However, up until now we haven't truncated when computing probabilities. This changes switches to always truncating our prediction. (This is a halfway house to a more rigorous approach which would condition the predicted distribution to be non-negative.) This should be good enough to ensure we never create non- zero anomaly scores for cases where actual equals typical equals zero except when the result is a multi-bucket anomaly.
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Backport #2270.