A Multiple Classifiers Integration Method Based on Adaptive Weigh Adjusting and it''''s Application on Text Classification
权重自适应调整的多分类器集成判决及其在文本分类中的应用

Multiple classifier systems based on the combination of a set of different classifiers are adopted to achieve high pattern-recognition performances. A multiple classifiers integration method based on adaptive weight adjusting is presented in this paper. The useful neighbors are selected from training set by analyzing the pending pattern's character, then each classifier's weight can be determined automatically by analyzing the performance of the classifier on the useful neighborhood set. The final output of the multiple classifiers systems is the effective integration of each calssifi-er's result. The effectiveness of the method is proved by the text classification experiments of the Reuters-21578 text sets.