Invention Grant
- Patent Title: Anomaly detection based on relationships between multiple time series
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Application No.: US15420737Application Date: 2017-01-31
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Publication No.: US10375098B2Publication Date: 2019-08-06
- Inventor: Adam Jamison Oliner , Jonathan La , Colleen Kinross , Hongyang Zhang , Jacob Leverich , Shang Cai , Mihai Ganea , Alex Cruise , Toufic Boubez , Manish Sainani
- Applicant: SPLUNK INC.
- Agency: Shook Hardy & Bacon LLP
- Main IPC: H04L29/06
- IPC: H04L29/06 ; G06N3/04 ; G06N3/08

Abstract:
In some implementations, sequences of time series values determined from machine data are obtained. Each sequence corresponds to a respective time series. A plurality of predictive models is generated for a first time series from the sequences of time series values. Each predictive model is to generate predicted values associated with the first time series using values of a second time series. For each of the plurality of predictive models, an error is determined between the corresponding predicted values and values associated with the first time series. A predictive model is selected for anomaly detection based on the determined error of the predictive model. Transmission is caused of an indication of an anomaly detected using the selected predictive model.
Public/Granted literature
- US20180219889A1 ANOMALY DETECTION BASED ON RELATIONSHIPS BETWEEN MULTIPLE TIME SERIES Public/Granted day:2018-08-02
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