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GECCO
2007
Springer

Support vector regression for classifier prediction

9 years 4 months ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifier exploits a Support Vector Machine to compute the prediction. In XCSF with support vector prediction, XCSFsvm, the genetic algorithm adapts classifier conditions, classifier actions, and the SVM kernel parameters. We compare XCSF with support vector prediction to XCSF with linear prediction on the approximation of four test functions. Our results suggest that XCSF with support vector prediction compared to XCSF with linear prediction (i) is able to evolve accurate approximations of more difficult functions, (ii) has better generalization capabilities and (iii) learns faster. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning--Learning Classifier Systems General Terms Algorithms, Performance Keywords Learning Classifier Systems , Support Vector Machines, Computed Prediction, XCS, Gen...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2007
Where GECCO
Authors Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
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