Disclosed is a local feature-based multi-view classifier, comprising: an unlabeled multi-view big data set generation module, a global and local structural risk minimization classifier implementation module and a multi-view data local feature extraction module. The advantage of the present invention is: by means of three aspects, i.e. effective data enhancement, classifier design principle construction and local feature extraction, the classification performance of a multi-view data set is effectively improved.
LOCAL FEATURE-BASED MULTI-VIEW CLASSIFIER AND DESIGN METHOD