Lines Matching refs:anomaly

4 …unctionalities it supports are anomaly detection and correlation. It can be used to investigate po…
5 …anomaly and gives you back a time window where the anomaly happened in, a time stamp where the ano…
8 …anomaly detection or correlation. In addition, the library does not rely on any predefined thresho…
12 * Get the anomaly period of the spike, and correlate with other system metrics(GC, IO, CPU, etc.) i…
36 2. conduct anomaly detection on a single time series ts.
42 3. if there is anomaly, correlate the first anomaly period with a secondary time series ts2.
61 _class_ luminol.modules.anomaly.**Anomaly**
64 self.start_timestamp: # epoch seconds represents the start of the anomaly period.
65 self.end_timestamp: # epoch seconds represents the end of the anomaly period.
66 self.anomaly_score: # a score indicating how severe is this anomaly.
67 self.exact_timestamp: # epoch seconds indicates when the anomaly reaches its severity.
101 *  `time_series`: The metric you want to conduct anomaly detection on. It can have the following th…
109 * `score only(bool)`: if asserted, anomaly scores for the time series will be available, while anom…
110 * `score_threshold`: if passed, anomaly scores above this value will be identified as anomaly. It c…
111 * `score_precentile_threshold`: if passed, anomaly scores above this percentile will be identified …
112 * `algorithm_name(string)`: if passed, the specific algorithm will be used to compute anomaly score…
114 …e specific algorithm will be used to compute the time stamp of severity within each anomaly period.
147 * `get_all_scores()`: returns a anomaly score time series of type [TimeSeries](#modules).
159 * `use_anomaly_score(bool)`: if asserted, the anomaly scores of the time series will be used to com…
179 1. Put anomaly scores in a list.
191 2. Correlate with ts2 on every anomaly.