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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Rodriguez, A., Acray, B., Dafonte, C., Manteiga, M., Carricajo, I.: Automated Knowledge-based Analysis and Classification of Stellar Spectra Using Fuzzy Reasoning. Expert Systems with Applications 27, 237–244 (2004)
Odewahn, S.C., Stockwell, E.B., Pennington, R.L., Humphreys, R.M., Zumach, W.A.: Automated Star/Galaxy Discrimination with Neural Networks. Astronomical Journal 103, 318–331 (1992)
Jacobs, R.A., Jordan, M.I., Norlan, S.J., Hinton, G.E.: Adaptive Mixtures of Local Experts. Neural Computation 3, 79–87 (1991)
Yumlu, M.S., Gurgen, F.S., Okay, N.: Financial Time Series Prediction Using Mixture of Experts. In: Yazıcı, A., Şener, C. (eds.) ISCIS 2003. LNCS, vol. 2869, pp. 553–560. Springer, Heidelberg (2003)
Kurtz, M.J.: The MK Process and Stellar Classification. David Dunlap Observatory, Toronto (1984)
Jacoby, G.H., Hunter, D.A., Christian, C.A.: A Library of Stellar Spectra. The Astrophysical Journal Supplement Series 56, 257–281 (1984)
Donoho, D.L.: De-noising by Soft-Thresholding. IEEE Trans. on Information Theory 41, 613–627 (1995)
Starck, J.L., Siebenmorgen, R., Gredel, R.: Spectral Analysis Using the Wavelet Transform. The Astrophysical Journal 482, 1011–1020 (1997)
Jiang, Y.G., Guo, P.: Spectral Analysis and Recognition Using Multi-scale Features and Neural Networks. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3174, pp. 369–374. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jiang, Y., Guo, P. (2005). Mixture of Experts for Stellar Data Classification. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_50
Download citation
DOI: https://doi.org/10.1007/11427445_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25913-8
Online ISBN: 978-3-540-32067-8
eBook Packages: Computer ScienceComputer Science (R0)