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Co-training is a well-known semi-supervised learning technique that applies two basic learners to train the data source, which uses the most confident unlabeled data to augment labeled data in the learning process. In the paper, we use the diversity of class probability estimation (DCPE) between two learners and propose the DCPE co-training approach. The key idea is to use DCPE to predict labels for the unlabeled data in the training process. The experimental studies with UCI data demonstratedoi:10.1016/j.neucom.2012.01.006 fatcat:pldazxyfmnbtrlux4yu4tf44uy