An Excellent Feature Selection Model Using Gradient-Based and Point Injection Techniques
This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. One is to modify feature searching engines based on optimization theory, and the other is to improve the regularization capability using point injection techniques. The second topic is undoubtedly important in the situations where overfitting is likely to be met, for example, the ones with only small sample sets available. Synthetic and real data are used to demonstrate the contribution of our proposed strategies.
KeywordsFeature Selection Feature Subset Point Injection Classification Learning Filter Model
Unable to display preview. Download preview PDF.
- Al-Ani, A., Deriche, M.: Optimal feature selection using information maximisation: case of biomedical data. In: Proc. of the 2000 IEEE Signal Processing Society Workshop, vol. 2, pp. 841–850 (2000)Google Scholar
- Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, New York (1995)Google Scholar
- Bonnlander, B.: Nonparametric Selection of Input Variables for Connectionist Learning, Ph.D. thesis, CU-CS-812-96, University of Colorado at Boulder (1996)Google Scholar
- Hall, M.A.: Correlation-based Feature Selection for Machine Learning, Ph.D. thesis, Department of Computer Science, Waikato University, New Zealand (1999)Google Scholar
- Han, J.W., Kamber, M.: Data mining: concepts and techniques. Morgan Kaufmann Publishers, San Francisco (2001)Google Scholar
- Molina, L.C., Belanche, L., Nebot, A.: Feature Selection Algorithms: a Survey and Experimental Evaluation, Technical Report (2002), available at: http://www.lsi.upc.es/dept/techreps/html/R02-62.html
- Wolf, L., Martin, I.: Regularization through feature knock out, AI memo 2004-2005 (2004), available at http://cbcl.mit.edu/cbcl/publications/ai-publications/2004/
- Zagoruiko, N.G., Elkina, V.N., Temirkaev, V.S.: ZET-an algorithm of filling gaps in experimental data tables. Comput. Syst. 67, 3–28 (1976)Google Scholar