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This paper improves a method of sample selection based on maximum entropy. Compared with the original method, the improved one takes the probability distribution of unlabeled instances into consideration. It selects the instances which can reduce the uncertainty of the whole unlabeled set to a great extent. The uncertainty reduction of the whole unlabeled set caused by an instance is measured by the...
Fuzzy production rules (FPRs) are widely used in expert systems to represent uncertainty concepts. In order to enhance the representation capability and to improve the reasoning-accuracy of FPRs, some useful knowledge representation parameters such as certainty factor, local weight and global weight have been included in FPRs. However, the acquisition of the values of these parameters is difficult...
When the fuzzy production rules (FPRs) are used for knowledge representation in rule-based system, overlapping exists among these rule sets corresponding to different classes. Each of the rule sets is composed of the rules which have the same consequence. In order to model and handle this kind of overlapping, this paper proposes a nonnegative non-additive set function and provides a new algorithm...
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