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Dynamic Feature Selection Algorithm Based on Minimum Vertex Cover of Hypergraph

  • Xiaojun Xie
  • Xiaolin Qin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10939)

Abstract

Feature selection is an important pre-processing step in many fields, such as data mining, machine learning and pattern recognition. This paper focuses on dynamically updating a subset of features with new samples arriving and provides a hypergraph model to deal with dynamic feature selection problem. Firstly, we discuss the relationship between feature selection of information system and minimum vertex cover of hypergraph, and feature selection is converted to a minimum vertex cover problem based on this relationship. Then, an algorithm for generating induced hypergraph from information system is presented, the induced hypergraph can be divided into two part: the original induced hypergraph and the added hypergraph with new samples arriving. Finally, a novel dynamic feature selection algorithm based on minimum vertex cover of hypergraph is proposed, and this algorithm only needs a small amount of computation. Experiments show that the proposed method is feasible and highly effective.

Keywords

Feature selection Hypergraph Minimum vertex cover Dynamic reduct 

Notes

Acknowledgments

The research was supported by The National Natural Science Foundation of China (grant nos. 61373015, 41301047, 61300052).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjingChina

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