Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Machine learning: an artificial intelligence approach volume III
Machine learning: an artificial intelligence approach volume III
C4.5: programs for machine learning
C4.5: programs for machine learning
Variable precision rough set model
Journal of Computer and System Sciences
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Dynamic Reducts as a Tool for Extracting Laws from Decisions Tables
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
Analytical Morphology: Mathematical Morphology Of Decision Tables
Fundamenta Informaticae
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In this paper we present some strategies for synthesis of decision algorithms studied by us. These strategies are used by systems of communicating agents and lead from the original (input) data table to a decision algorithm. The agents are working with parts of data and they compete for the decision algorithm with the best quality of object classification. We give examples of techniques for searching for new features and we discuss some adaptive strategies based on the rough set approach for the construction of a decision algorithm from a data table. We also discuss a strategy of clustering by tolerance.