Computer Science ›› 2013, Vol. 40 ›› Issue (3): 266-270.
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Abstract: To improve the performance of ensemble learning, an ensemble algorithm which is a combination of Rotation Forest and Mu1tiI3oost was proposed as follows:To improve the diversity between classifiers,rotation transformation in rotation forest is introduced to model the new data set, and for higher accuracy, each classifier is trained by MultiBoost on the transformed data set. Finally,majority voting method is utilized to fusion the base classifiers' recognition results.To attest the validity, we made experiments on UCI data sets. The experimental results suggest that our algorithm can get higher classification accuracy.
Key words: Ensemble learning,Support vector machine,Random projection,Rotation forest,MultiBoost
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