SVM Kernels for Time Series Analysis
Date
2001
Authors
Journal Title
Journal ISSN
Volume Title
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.
Description
Table of contents
Keywords
support vector machines, time series