Large Scale Classification Based on Combination of Parallel SVM and Interpolative MDS
With the development of information technology, the scale of electronic data becomes larger and larger. Data deluge occurs in many kinds of application fields. How to explore the useful information from the large scale dataset is a very important issue. Data mining is just to take on the task. Support Vector Machines (SVM) is a powerful classification and regression tools of data mining. It has been widely studied by many scholars and applied in many kinds of practical fields. But its compute and storage requirements increase rapidly with the number of training vectors, putting many problems of practical interest out of their reach.