Combining SVMs with Various Feature Selection Strategies

• Main Authors: Yi-Wei Chen, 陳奕瑋
• Other Authors: Chih-Jen Lin
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/94847510804922841814

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 93 === Feature selection is an important issue in many research areas. There are some reasons for selecting important features such as reducing the learning time, improving the accuracy, etc. This thesis investigates the performance of combining support vector machines (SVM) and various feature selection strategies. The first part of the thesis mainly describes the existing feature selection methods and our experience on using those methods to attend a competition. The second part studies more feature selection strategies using the SVM.