Mixture of experts for stellar data classification

Authors:
Yugang Jiang;Ping Guo
Affiliations:
Department of Computer Science, Beijing Normal University, Beijing, China;Department of Computer Science, Beijing Normal University, Beijing, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

Citing 2
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Abstract

In this paper, mixture of experts model is first applied to stellar data classification. In order to obtain input patterns of mixture of experts model, we present a feature extraction method for stellar data based on wavelet packet transformation. Then a mixture of experts model is built for classifying the feature vectors. A comparative study of different classification methods such as a single radial basis function neural network is given. Real world data experimental results show that the mixture of experts has a good generalization ability and the obtained correct classification rate is higher than that of using a single neural network.