| 英文标题 | Survey of semi-supervised feature selection methods |
| 作者英文名 | Zhang Dongfang, Chen Haiyan, Wang Jiandong |
| 机构英文名 | a.School of Computer Science & Technology,b.Collaborative Innovation Center of Novel Software Technology & Industrialization,Nanjing University of Aeronautics & Astronautics,Nanjing 211100,China |
| 英文摘要 | How to select features on semi-supervised data sets by incomplete supervisory information has become a research hotspot in the field of pattern recognition and machine learning. In order to facilitate researchers to systematically understand the research status and development trend of semi-supervised feature selection, this paper reviewed the semi-supervised feature selection methods. This paper first discussed the classification of semi-supervised feature selection methods and divided them into graph-based methods, pseudo-label-based methods, SVM-based methods and other methods according to their theoretical basis, then introduced and compared typical methods for each category, and then sorted out hot applications of semi-supervised feature selection. Finally, this paper looked forward to the future research directions of semi-supervised feature selection. |
| 英文关键词 | machine learning; semi-supervised learning; feature selection |