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This paper presents an improved method of selective ensemble to filter the spam messages. The design adopts clustering based on the diversity between sub-classifiers to solve the problem of selection. To improve accuracy and stability, a conception of confidence weight is proposed to evaluate the reliability of selected sub-classifiers. The training model is created with small datasets as in the real...
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