Combining Evolutionary, Connectionist, and Fuzzy Classification Algorithms for Shape Analysis
نویسندگان
چکیده
This paper presents an investigation into the classification of a difficult data set containing large intra-class variability but low inter-class variability. Standard classifiers are weak and fail to achieve satisfactory results however, it is proposed that a combination of such weak classifiers can improve overall performance. The paper also introduces a novel evolutionary approach to fuzzy rule generation for classification problems.
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