International Business Machines Corporation
TRIPLET GENERATION FOR REPRESENTATION LEARNING IN TIME SERIES USING DISTANCE BASED SIMILARITY SEARCH

Abstract:

A method of using a computing device to train a neural network to recognize features in variate time series data that includes receiving, by a computing device, variate time series data. The computing device further receives results associated with the variate time series data. The computing device determines an anchor of the variate time series data. The computing device additionally determines one or more portions of the variate time series data which lead to a positive result. The computing device further determines one or more portions of the variate time series data which lead to a negative result. The computing device trains a neural network to interpret results of future variate time series data based upon the anchor, the one or more portions of the variate time series data which lead to the positive result, and the one or more portions of the variate time series data which lead to the negative result.