Tutorial on the Support Vector Machine and Boosting:a Statistical Perspective
主 题: Tutorial on the Support Vector Machine and Boosting:a Statistical Perspective
报告人: Ji Zhu (Statistics, University of Michigan)
时 间: 2007-08-29 下午 2:30
地 点: 理科一号楼 1303
The support vector machine and boosting are widely used tools for predicting or classifying noisy data. The ideas were introduced by Vapnik (1995) and Freund & Schapire (1996). These two methods have attracted a lot of attention due to their great success in data modeling tasks. They are now being applied to medical diagnosis, bioinformatics and genetic modeling, chemical process control, shape, handwriting, speech and face recognition, financial modeling, and a wide range of other important practical problems. In this talk, I will give a tutorial on these two methods, from the point of view of a statistician.
