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[ML] Modify thresholds for normalization triggers The (arbitrary) threshold factors used to judge if scores have changed significantly enough to trigger a look-back renormalization have been changed to values that reduce the frequency of such renormalizations. Added a clause to treat changes in scores as a 'big change' if it would result in a change of severity reported in the UI. Also altered the clause affecting small scores so that a change should be considered big if scores have changed by at least 1.5. Relates https://github.com/elastic/machine-learning-qa/issues/263
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