An efficient and accurate optimization method of sliding window size for PAA
Jinyang Liu, Chuanlei Zhang, Shanwen Zhang, Weidong Fang · 2014
PAA is an important algorithm in time series dimensionality reduction. However, how to determine the sliding window keeps an open issue for PAA and its derivatives. In this paper, a new optimization method to decide the PAA window is proposed based on root mean square distance measure. A rate of information loss is proposed to overcome the scalability issue, which can be used to balance information loss and query performance improvement caused by PAA transformation. Experiment results with a real time series dataset demonstrate that the method is effective and feasible to determine the PAA window size and optimize the whole performance of PAA algorithm.