Boolean factor analysis for data preprocessing in machine learning

Proceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010

Volumn , Issue , 2010, Pages 899-902

  Outrata, Jan ^a  

^a PALACKÝ UNIVERSITY   (Czech Republic)

Author keywords

Data preprocessing; Decision trees; Formal concept; Machine learning; Matrix decomposition

Indexed keywords

BENCHMARK DATASETS; COMPARISON OF PERFORMANCE; DATA PREPROCESSING; DECISION TREE INDUCTION; EXPERIMENTAL EVALUATION; FACTOR ANALYSIS; FORMAL CONCEPT; FORMAL CONCEPT ANALYSIS; INPUT DATAS; MACHINE-LEARNING; MATRIX DECOMPOSITION;

INPUT OUTPUT PROGRAMS; LEARNING SYSTEMS;

DECISION TREES;

EID: 79952373637     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2010.141     Document Type: Conference Paper

References (15)

1. R. Belohlavek and V. Vychodil: Discovery of optimal factors in binary data via a novel method of matrix decomposition. J. Comput. System Sci 76(1)(2010), 3-20.
2. L. Breiman, J. H. Friedman, R. Olshen and C. J. Stone: Classification and Regression Trees. Chapman & Hall, NY, 1984.
3. C. Carpineto and G. Romano: Concept Data Analysis. Theory and Applications. J. Wiley, 2004.
4. B. Ganter and R. Wille: Formal Concept Analysis. Mathematical Foundations. Springer, Berlin, 1999.
5. Harman H. H.: Modern Factor Analysis, 2nd Ed. The Univ. Chicago Press, 1970.
6. K. H. Kim: Boolean Matrix Theory and Applications. M. Dekker, 1982.
7. R. S. Michalski: A theory and methodology of inductive learning. Artificial Intelligence 20(1983), 111-116.
8. P. M. Murphy and M. J. Pazzani: ID2-of-3: constructive induction of M-of-N concepts for discriminators in decision trees. In Proc. of the Eight Int. Workshop on Machine Learning, 1991, 183-187.
9. S. K. Murthy: Automatic construction of decision trees from data. Data Mining and Knowledge Discovery 2, 1998, 345-389.
10. S. K. Murthy, S. Kasif and S. Salzberg: A system for induction of oblique decision trees. J. of Artificial Intelligence Research 2(1994), 1-33.
11. D. J. Newman, S. Hettich, C. L. Blake and C. J. Merz: UCI Repository of machine learning databases, [http://www.ics.uci.edu/~mlearn/MLRepository.html], University of California, Dept. of Information and Computer Science, 1998.
12. G. Pagallo and D. Haussler: Boolean feature discovery in empirical learning. Machine Learning 5(1)(1990), 71-100.
13. J. R. Quinlan: C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.
14. P. N. Tan, M. Steinbach and V. Kumar: Introduction to Data Mining. Addison Wesley, Boston, MA, 2006.
15. I. H. Witten and E. Frank: Data Mining: Practical machine learning tools and techniques, 2nd Edition. Morgan Kaufmann, San Francisco, 2005.