Comparison of rough-set and statistical methods in inductive learning
International Journal of Man-Machine Studies
International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Machine learning and uncertain reasoning
Machine learning and uncertain reasoning
Variable precision rough set model
Journal of Computer and System Sciences
Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory
Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Readings in Machine Learning
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Variable Precision Rough Sets with Asymmetric Bounds
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
An Incremental Learning Algorithm for Constructing Decision Rules
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
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This paper presents an approach to incremental concept learning in attribute-value systems. The main characteristic feature of this approach is adaptive creation of a complete decision table rather than classification rules. The approach involves gradual accumulation of atomic class descriptions followed by subsequent analysis and simplification of the learned decision table using the ideas of rough sets. Both deterministic and probabilistic aspects of learning are discussed. The basic learning procedure is presented. The convergence of the learning process is illustrated with a computational example using the Thyroid data collection.