In order to boost the diversity among individual classifiers of an ensemble,a new ensemble method is proposed that combines two different classifier models via a transformation of rotation forest,named by isomerous multiple classifier ensemble.Firstly,the original samples are transformed and divided by the rotating forest to obtain new samples.Then support vector machine with the high accuracy of classification or kernel matching pursuit with the speedy classification is selected as a basic classifier model...
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