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The goal of ensemble construction with several classifiers is to achieve better generalization ability over individual classifiers. An ensemble method produces diverse classifiers and combines their decisions for ensemble's decision. A number of methods have been investigated for constructing ensemble in which some of them train classifiers with the generated patterns. This study investigates a decision...
The goal of an ensemble construction with several classifiers is to achieve better generalization than that of a single classifier. And proper diversity among classifiers is considered as the condition for an ensemble construction. This paper investigates synthetic pattern for diversity among classifiers. It alters input feature values of some patterns with the values of other patterns to get synthetic...
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