On Multiple Classi er Systems for Pattern Recognition
نویسندگان
چکیده
Diicult pattern recognition problems involving large class sets and noisy input can be solved by a multiple classiier system, which allows simultaneous use of arbitrary feature descriptors and classiication procedures. Independent decisions by each classiier can be combined by methods of the highest rank, Borda count, and logistic regression, resulting in substantial improvement in overall correctness.
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