def _denoise_scores(self, scores):
if scores:<EOL><INDENT>maximal = max(scores.values())<EOL>if maximal:<EOL><INDENT>for key in scores:<EOL><INDENT>if scores[key] < DEFAULT_NOISE_PCT_THRESHOLD * maximal:<EOL><INDENT>scores[key] = <NUM_LIT:0><EOL><DEDENT><DEDENT><DEDENT><DEDENT>return scores<EOL>
Denoise anomaly scores.
Low anomaly scores could be noisy. The following two series will have good correlation result with out denoise:
[0.08, 4.6, 4.6, 4.6, 1.0, 1.0]
[0.0010, 0.0012, 0.0012, 0.0008, 0.0008]
while the second series is pretty flat(suppose it has a max score of 100).
param dict scores: the scores to be denoised.