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Rüping, Stefan
Year of Publication: 
Series/Report no.: 
Technical Report, SFB 475: Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2001,43
Time series analysis is an important and complex problem in machine learning and statistics. Real-world applications can consist of very large and high dimensional time series data. Support Vector Machines (SVMs) are a popular tool for the analysis of such data sets. This paper presents some SVM kernel functions and discusses their relative merits, depending on the type of data that is used.
Support Vector Machines
Time Series
Document Type: 
Working Paper

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