Machine learning of credible classifications

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1342, Issue , 1997, Pages 330-339

  Hamilton, Howard J ^a   Shan, Ning ^a   Ziarko, Wojciech ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

CONCEPT DISCOVERIES; CONDITION ATTRIBUTES; QUALITY CRITERIA;

MACHINE LEARNING;

EID: 84961356873     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-63797-4_86     Document Type: Conference Paper

References (13)

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8. S. K. Murthy and S. Salzberg. Decision tree induction: How effective is the greedy heuristic? In Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD-96), pages 222-227, Portland, OR, 1996.
9. Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer, 1991.
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11. N. Shan, H. J. Hamilton, and N. Cercone. GRG: Knowledge discovery using information generalization, information reduction, and rule generation. International Journal of Artificial Intelligence Tools, 5(1 & 2):99-112, 1996.
12. N. Shan, H. J. Hamilton, W. Ziarko, and N. Cercone. Discovering classification knowledge in databases using rough sets. In Proc. of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD'96), pages 271-274, Portland, OR, 1996.
13. N. Shan, H. J. Hamilton, W. Ziarko, and N. Cercone. Discretization of continuous valued attributes in attribute-value systems. In Proc. of the Fourth Int'l. Workshop on Rough Sets, Fuzzy Sets, and Machine Discovery (RFSD'96), pages 74-81, Tokyo, Japan, 1996.