Design for target classifier based on semi-supervised learning

The target classifier is an ingredient of the target recognition system. In order to achieve the automation and computerization of target recognition, a method for training target classifier based on semi-supervised learning is provided. It adopts CFS algorithm for dada feature selection, and uses semi supervised learning algorithm, Co-training to construct the target classifiers. The final classifier was produced through integration learning method. Experimental results show that the performance of the target classifier based on semi-supervised learning trained is superior to the traditional target classifier.