关键词: 主动学习, 采样查询, 加权投票, 熵, 标注门槛

Abstract: In this paper, a method of weighted voting is proposed which can adjust weights of classifiers in committee during the sampling process and it is based on query by committee algorithm. In process of unlabeled sample’s quality evaluation, the method can strengthen the contribution of high precision members, reduce the influence of high error members and decrease the times of learning which is needed in machine training. By experiment on dataset of Statlog（Australian Credit Approval）and compared results with other methods, the effectiveness has been proved that the algorithm can gain stable generalization accuracy with smaller costs of samples labeling.

Key words: active learning, sampling query, weighted voting, entropy, labeling threshold