Invention Application
- Patent Title: UNSUPERVISED METHOD FOR CLASSIFYING SEASONAL PATTERNS
-
Application No.: US15057062Application Date: 2016-02-29
-
Publication No.: US20170249563A1Publication Date: 2017-08-31
- Inventor: Dustin Garvey , Uri Shaft , Lik Wong
- Applicant: Oracle International Corporation
- Main IPC: G06N99/00
- IPC: G06N99/00 ; G06N5/04

Abstract:
Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.
Public/Granted literature
- US10885461B2 Unsupervised method for classifying seasonal patterns Public/Granted day:2021-01-05
Information query