Combined Classifiers for Time Series Shapelets
Ivan S. Mitzev, Nickolas H. Younan · 2016
Time-series classification is widely used approach for classification.Recent development known as time-series shapelets, based on local patterns from the time-series, shows potential as highly predictive and accurate method for data mining.On the other hand, the slow training time remains an acute problem of this method.In recent years there was a significant improvement of training time performance, reducing the training time in several orders of magnitude.This work tries to maintain low training time-in the range from several second to several minutes for datasets from the popular UCR database, achieving accuracies up to 20% higher than the fastest known up to date method.The goal is achieved by training small 2,3-nodes decision trees and combining their decisions in pattern that uniquely identifies incoming time-series.