Time series classification in the dissimilarity space combines the advantages of the dynamic time warping and the rich mathematical structure of Euclidean spaces. We applied dimension reduction using PCA followed by support vector learning on dissimilarity representations to 43 UCR datasets. Results indicate that time series classification in dissimilarity space has potential to complement the state-of-the-art.
['Brijnesh J. Jain', 'Stephan Spiegel']
Time Series Classification in Dissimilarity Spaces