Abstract
Change Point Discovery (CPD) and Constrained Motif Discovery (CMD) are two essential problems in data mining with applications in many fields including robotics, economics, neuroscience and other fields. In this paper, we show that these two problems are related and report the development of a MATLAB Toolbox (CPMD) that encapsulates several useful algorithms including new variants to solve these two related problems. The Toolbox is then used to study the effect of distance function choice in CPD.
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CPMD Toolbox, http://www.ii.ist.i.kyoto-u.ac.jp/~yasser/cpmd/cpmd.html
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Mohammad, Y., Ohmoto, Y., Nishida, T. (2012). CPMD: A Matlab Toolbox for Change Point and Constrained Motif Discovery. In: Jiang, H., Ding, W., Ali, M., Wu, X. (eds) Advanced Research in Applied Artificial Intelligence. IEA/AIE 2012. Lecture Notes in Computer Science(), vol 7345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31087-4_13
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DOI: https://doi.org/10.1007/978-3-642-31087-4_13
Publisher Name: Springer, Berlin, Heidelberg
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