Rank Aggregation Based Text Feature Selection

Filtering feature selection method (filtering method, for short) is a well-known feature selection strategy in pattern recognition and data mining. Filtering method outperforms other feature selection methods in many cases when the dimension of features is large. There are so many filtering methods proposed in previous work leading to the “selection trouble” that how to select an appropriate filtering method for a given text data set. Since to find the best filtering method is usually intractable in real application, this paper takes an alternative path. We propose a feature selection framework that fuses the results obtained by different filtering methods. In fact, deriving a better rank list from different rank lists, known as rank aggregation, is a hot topic studied in many disciplines. Based on the proposed framework and Markov chains rank aggregation techniques, in this paper, we present two new feature selection methods: FR-MC1 and FR-MC4. We also introduce a perturbation al...

• Type: Conference
• Year: 2009
• Where: WEBI
• Authors: Ou Wu, Haiqiang Zuo, Mingliang Zhu, Weiming Hu, Jun Gao, Hanzi Wang
• Keywords: Feature Selection, Feature Selection Methods, Filtering Methods, Internet Technology, WEBI 2009