SVM Kernels for Time Series Analysis

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Date

2001

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Publisher

Universitätsbibliothek Dortmund

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.

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Keywords

support vector machines, time series

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