Authors: Rüping, Stefan
Title: SVM Kernels for Time Series Analysis
Language (ISO): en
Abstract: 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 disusses their relative merits, depending on the type of data that is used.
Subject Headings: support vector machines
time series
URI: http://hdl.handle.net/2003/5258
http://dx.doi.org/10.17877/DE290R-15237
Issue Date: 2001
Publisher: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

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