Research and Application of Digital Media Object Classification Method Based on Large Interval Distribution Learning

Digital media object classification plays an important role in digital media, but there is a problem of low classification accuracy. Deep learning algorithms cannot improve the accuracy of digital media object classification. Therefore, this paper proposes a large-interval distribution learning algorithm to classify digital media objects. Digital media objects are analyzed through distributed learning, and indicators are divided according to classification requirements. The large interval distribution learning algorithm forms the digital media object classification scheme, and the formed classification scheme is comprehensively analyzed. The simulation results show that the classification accuracy and classification efficiency of the proposed algorithm are better than those of the deep learning algorithm.