Supervised pattern recognition by parallel feature partitioning

Pattern Recognition

Volumn 37, Issue 3, 2004, Pages 463-467

  Valev, Ventzeslav ^a  

^a Saint Louis University   (United States)

Author keywords

Integer valued optimization; Parallel feature partitioning; Supervised pattern recognition

Indexed keywords

MATHEMATICAL MODELS; OPTIMIZATION; PROBLEM SOLVING;

PARALLEL FEATURE PARTITIONING;

PATTERN RECOGNITION;

PATTERN RECOGNITION;

EID: 0347478107     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2003.09.003     Document Type: Article

References (9)

1. Güvenir H.A. Sirin I. Classification by feature partitioning Mach. Learn. 23 1996 47-67
2. Aha D.W. Kibler D. Albert M.K. Instance based learning algorithms Mach. Learn. 6 1991 66-77
3. Rendell L. A new basis for state-space learning systems and successful implementation Artif. Intell. 20 1983 369-392
4. Salzberg S. A nearest hyperrectangle method Mach. Learn. 6 1991 251-276
5. Quinlan J.R. Induction of decision trees Mach. Learn. 1 1986 81-106
6. V. Valev, On the representation of training tables in a k-valued code and the construction of empirical regularities, Proceedings of Ninth International Conference on Pattern Recognition, Vol. II, Rome, 14-17 November 1988, IEEE Computer Society Press, 1988, pp. 779-781.
7. Valev V. Zhuravlev Yu. Integer-valued problems of transforming the training tables in k-valued code in pattern recognition problems Pattern Recognition 24 4 1991 283-288
8. M. Garey, D. Johnson, Computers and Intractability, A Guide to the Theory of NP-Completeness, Bell Teleph. Lab., New Jersey, 1979.
9. Hamming R. Coding and Information Theory 1980 Prentice-Hall Englewood Cliffs, NJ