Regression based on support vector classification

Authors:
Marcin Orchel
Affiliations:
AGH University of Science and Technology, Kraków, Poland
Venue:
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
Year:
2011

Citing 2
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Abstract

In this article, we propose a novel regression method which is based solely on Support Vector Classification. Experiments show that the new method has comparable or better generalization performance than ε-insensitive Support Vector Regression. The tests were performed on synthetic data, on various publicly available regression data sets, and on stock price data. Furthermore, we demonstrate how a priori knowledge which has been already incorporated to Support Vector Classification for predicting indicator functions, could be directly used for a regression problem.