Feature selection for human resource selection based on affinity propagation and SVM sensitivity analysis

Qiangwei Wang, Boyang Li, Takayuki Furuzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Feature selection is a process to select a subset of original features. It can improve the efficiency and accuracy by removing redundant and irrelevant terms. Feature selection is commonly used in machine learning, and has been wildly applied in many fields. we propose a new feature selection method. This is an integrative hybrid method. It first uses Affinity Propagation and SVM sensitivity analysis to generate feature subset, and then use forward selection and backward elimination method to optimize the feature subset based on feature ranking. Besides, we apply this feature selection method to solve a new problem, Human resource selection. The data is acquired by questionnaire survey. The simulation results show that the proposed feature selection method is effective, it not only reduced human resource features but also increased the classification performance.

Original languageEnglish
Title of host publication2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings
Pages31-36
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Coimbatore
Duration: 2009 Dec 92009 Dec 11

Other

Other2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009
CityCoimbatore
Period09/12/909/12/11

Fingerprint

Sensitivity analysis
Feature extraction
Personnel
Set theory
Learning systems

Keywords

  • Affinity propagation
  • Feature selection
  • Human resource selection
  • SVM sensitivity analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Software

Cite this

Wang, Q., Li, B., & Furuzuki, T. (2009). Feature selection for human resource selection based on affinity propagation and SVM sensitivity analysis. In 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings (pp. 31-36). [5393596] https://doi.org/10.1109/NABIC.2009.5393596

Feature selection for human resource selection based on affinity propagation and SVM sensitivity analysis. / Wang, Qiangwei; Li, Boyang; Furuzuki, Takayuki.

2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings. 2009. p. 31-36 5393596.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, Q, Li, B & Furuzuki, T 2009, Feature selection for human resource selection based on affinity propagation and SVM sensitivity analysis. in 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings., 5393596, pp. 31-36, 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009, Coimbatore, 09/12/9. https://doi.org/10.1109/NABIC.2009.5393596
Wang Q, Li B, Furuzuki T. Feature selection for human resource selection based on affinity propagation and SVM sensitivity analysis. In 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings. 2009. p. 31-36. 5393596 https://doi.org/10.1109/NABIC.2009.5393596
Wang, Qiangwei ; Li, Boyang ; Furuzuki, Takayuki. / Feature selection for human resource selection based on affinity propagation and SVM sensitivity analysis. 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings. 2009. pp. 31-36
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