Research Survey on Support Vector Machine

Support vector machine (SVM) as a learning machine has shown a good learning ability and generalization ability in classification, regression and forecasting. Because of its excellent learning performance, SVM has always been a hotspot in machine learning. In hence, this paper will make a more systematic introduction of SVM, including the theory of SVM, the summarization and comparison of the quadratic programming optimizations and parameter optimizations for SVM and the introduction of some new SVMs, like FSVM, TSVM, MSVM, etc. Then, the applications of SVM in real life will be presented, especially, in the area of mobile multimedia. Finally, we conclude with a discussion of the direction of further SVM improvement.