Time Series Clustering Ensemble Algorithm Based on Locality Preserving Projection
Xue Liu · 2015
The time series clustering is one of the important research contents in the time series data mining.Since the dimension of time series is common high, the performance of direct raw time series data clustering is not ideal.How to improve the clustering performance of time series is the main research point of this paper.Firstly, use Locality Preserving Projection (LPP) to time series samples for dimensionality reduction; secondly, carry out clustering ensemble to the lowdimension data; finally, compare the clustering performance with the existing methods such as Principal Component Analysis (PCA) and Piecewise Aggregate Approximation (PAA).Experiment results show that the proposed method is superior to the compared methods.