Feature selection for high-dimensional data in astronomy

Advances in Space Research

Volumn 41, Issue 12, 2008, Pages 1960-1964

  Zheng, Hongwen ^a   Zhang, Yanxia ^b  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

^b CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Astronomical catalogs; Feature selection; Method: data analysis; Sky survey

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; FEATURE EXTRACTION; INFORMATION RETRIEVAL; SPACE RESEARCH;

ASTRONOMICAL CATALOGS; LOW-DIMENSIONAL SPACES;

ASTRONOMY;

EID: 43149098046     PISSN: 02731177     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asr.2007.08.033     Document Type: Article

References (18)

1. H. Almuallim T.G. Dietterich Learning boolean concepts in the presence of many irrelevant features Artificial Intelligence 69 1–2 1994 279 305
2. Dash, M., Choi, K., Scheuermann, P., Liu, H., Feature selection for clustering C a filter solution, in: Proceedings of the Second International Conference on Data Mining, pp. 115–122, 2002.
3. M. Dash H. Liu Feature selection for classification Intelligent Data Analysis: An International Journal 1 3 1997 131 156
4. I. Ferreras A. Pasquali R.R. de Carvalho A principal component analysis approach to the star formation history of elliptical galaxies in compact groups MNRAS 370 2006 828 836
5. I. Guyon A. Elisseeff An introduction to variable and feature selection Journal of Machine Learning Research 3 2003 1157 1182
6. Kira, K., Rendell, L.A. A practical approach to feature selection, in: Sleeman, D., Edwards, P. (Eds.), Machine Learning: Proceedings of International Conference (ICML92). Morgan Kaufmann, pp. 249–256, 1992.
7. R. Kohavi G.H. John Wrappers for feature subset selection Artificial Intelligence 97 1997 273 324
8. H. Liu H. Motoda Feature Selection for Knowledge Discovery and Data Mining 1998 Kluwer Boston
9. H. Lu H. Zhou J. Wang Ensemble learning for independent component analysis of normal galaxy spectra AJ 131 2 2006 790 805
10. A. Miller Subset Selection in Regression second ed. 2002 Chapman & Hall/CRC
11. T.M. Mitchell Machine Learning 1997 McGraw-Hill International Editions
12. J.R. Quinlan C4.5: Programs for Machine Learning 1993 Morgan Kaufmann
13. R. Rakotomalala D. Zighed Association measures in the induction graphs: a statistic approach of the generality-precision referring Proceedings of AIDRI’97 1997 131 134
14. P. Re Fiorentin C.A.L. Bailer-Jones Y.S. Lee Estimation of stellar atmospheric parameters from SDSS/SEGUE spectra A&A 467 3 2007 1373 1387
15. M. Robnik-Šikonja I. Kononenko Theoretical and empirical analysis of ReliefF and RReliefF Machine Learning Journal 53 2003 23 69
16. G. Saporta Probability, Analysis of Data and Statistics 1990 Technip
17. Zhang, Y., Luo, A., Zhao, Y., An automated classification algorithm for multiwavelength data, in: Quinn, P., Bridger, A. (Eds.), Optimizing Scientific Return for Astronomy through Information Technologies. Proceedings of SPIE 5493, pp. 483–490, 2004.
18. Y. Zhang Y. Zhao Automated clustering algorithms for classification of astronomical objects A&A 422 2004 1113 1121