Clustering and Visualization of Multivariate Time Series

The analysis of MTS is an established research area, and methods to carry it out have stemmed both from traditional statistics and from the Machine Learning and Computational Intelligence fields. In this chapter, we are mostly interested in the latter, but considering a mixed approach that can be ascribed to Statistical Machine Learning. MTS are often analyzed for prediction and forecasting and, therefore, the problem is considered to be supervised. In comparison, little research has been conducted on the problem of unsupervised clustering for the exploration of the dynamics of multivariate time series (Liao, 2005). It is sensible to assume that, in many problems involving MTS, the states of a process may be reproduced or revisited over time; therefore, clustering structure is likely to be found in the series. Furthermore, for exploratory purposes, it ABStrAct