Abstract:

Based on the AdaBoost ensemble framework,  a learning algorithm of generative／discriminative combination classifier was proposed. In each round of the algorithm, a generative classifier and a discriminative classifier were learned, and the classifier with the smaller error rate was selected as the individual classifier, and then all the individual classifiers were combined by a weighted approach. Experiment results showed  that this method was very good on accuracy and convergence speed.
 

Key words: generative models; discriminative models; ensemble classifier; individual classifier