Aggressive and effective feature selection using genetic programming

2012 IEEE Congress on Evolutionary Computation, CEC 2012

Volumn , Issue , 2012, Pages

  Sandin, Isac ^a   Andrade, Guilherme ^a   Viegas, Felipe ^a   Madeira, Daniel ^a   Rocha, Leonardo ^a   Salles, Thiago ^b   Gonçalves, Marcos ^b  

^a FEDERAL UNIVERSITY OF SÃO JOÃO DEL REI   (Brazil)

^b FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

AGGRESSIVE REDUCTION; AUTOMATIC CLASSIFICATION; CORRELATION COEFFICIENT; DATA SETS; DIMENSIONALITY REDUCTION; INFORMATION GAIN; INPUT SPACE; NUMBER OF SAMPLES; P53 PROTEIN; REAL WORLD DATA; SELECTION OF ATTRIBUTES; SKEWED DATA; UNBIASED ESTIMATES;

LEARNING ALGORITHMS; VIRTUAL REALITY;

GENETIC PROGRAMMING;

EID: 84866840233     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2012.6252878     Document Type: Conference Paper

References (15)

1. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, ser. Springer Series in Statistics. New York, NY, USA: Springer New York Inc., 2001.
2. F. Sebastiani and C. N. D. Ricerche, "Machine learning in automated text categorization," ACM Computing Surveys, vol. 34, pp. 1-47, 2002.
3. Y. Yang and J. O. Pedersen, "A comparative study on feature selection in text categorization," in Proceedings of the Fourteenth International Conference on Machine Learning, ser. ICML '97. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 1997, pp. 412-420. [Online]. Available: http://dl.acm.org/citation.cfm?id=645526.657137
4. G. Forman, "An extensive empirical study of feature selection metrics for text classification," The Journal of Machine Learning Research, vol. 3, pp. 1289-1305, 2003.
5. D. Mladenic, "Machine learning on non-homogeneous, distributed text data." Ph.D. dissertation, University of Ljubljana, Faculty of Computer and Information Science, 1998.
6. H. T. Ng, W. B. Goh, and K. L. Low, "Feature selection, perceptron learning, and a usability case study for text categorization," in Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval, ser. SIGIR '97. New York, NY, USA: ACM, 1997, pp. 67-73. [Online]. Available: http://doi.acm.org/10.1145/258525. 258537
7. I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (The Morgan Kaufmann Series in Data Management Systems), 1st ed. Morgan Kaufmann, Oct. 1999.
8. Z. Zheng, X. Wu, and R. Srihari, "Feature selection for text categorization on imbalanced data," ACM SIGKDD Explorations Newsletter, vol. 6, pp. 80-89, 2004.
9. X.-w. Chen and M. Wasikowski, "Fast: a roc-based feature selection metric for small samples and imbalanced data classification problems," in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ser. KDD '08, 2008, pp. 124-132.
10. H. Park, S. Kwon, and H.-C. Kwon, "Complete gini-index text (git) feature-selection algorithm for text classification," in Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on, 2010, pp. 366-371.
11. W. Shang, H. Huang, H. Zhu, Y. Lin, Y. Qu, and Z. Wang, "A novel feature selection algorithm for text categorization," vol. 33, no. 1, 2007.
12. J. R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection (Complex Adaptive Systems). Cambridge, MA, USA: The MIT Press, 1992.
13. S. A. Danziger, R. Baronio, L. Ho, L. Hall, K. Salmon, G. W. Hatfield, P. Kaiser, and R. H. Lathrop, "Predicting positive p53 cancer rescue regions using most informative positive (mip) active learning," PLoS Comput Biol, vol. 5, no. 9, 09 2009.
14. D. D. Lewis, "Evaluating and optimizing autonomous text classification systems," in Eighteenth Annual, International ACM-SIGIR Conference on Research and Development in Information Retrieval, 1995, pp. 264- 254.
15. T. Weinbrenner, "Genetic programming techniques applied to measurement data," Diploma Thesis, Germany, February 1997. [Online]. Available: http://citeseer.ist.psu.edu/weinbrenner97genetic.html