Using feature selection to reduce the complexity in analyzing the injury severity of traffic accidents

Jo Ting Wei; Hsin Hung Wu; Kuang Yang Kou

doi:10.1109/IJCSS.2011.73

Using feature selection to reduce the complexity in analyzing the injury severity of traffic accidents

Jo Ting Wei, Hsin Hung Wu, Kuang Yang Kou

Department of Business Administration

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

When analyzing the traffic accidents in terms of predicting injury severity, past studies often use too many variables and thus lead to over fitting and complicate the interpretation of the analysis. By adopting feature selection technique, irrelevant and redundant features from a dataset will be filtered out such that high discrimination power and informative features will be provided. This paper selects twenty eight factors by adopting feature selection to analyze the injury severity of traffic accidents in Taiwan. The method facilitates to reduce the complexity of analyzing the injury severity of traffic accidents. The findings show that nineteen factors are classified into important; one is categorized as marginal; and five are grouped into unimportant.

Original language	English
Title of host publication	Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011
Pages	329-333
Number of pages	5
DOIs	https://doi.org/10.1109/IJCSS.2011.73
Publication status	Published - 2011 Sep 5
Event	2011 International Joint Conference on Service Sciences, IJCSS 2011 - Taipei, Taiwan Duration: 2011 May 25 → 2011 May 27

Publication series

Name	Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011

Other

Other	2011 International Joint Conference on Service Sciences, IJCSS 2011
Country	Taiwan
City	Taipei
Period	11-05-25 → 11-05-27

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All Science Journal Classification (ASJC) codes

Management of Technology and Innovation

Cite this

Wei, J. T., Wu, H. H., & Kou, K. Y. (2011). Using feature selection to reduce the complexity in analyzing the injury severity of traffic accidents. In Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011 (pp. 329-333). [5960374] (Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011). https://doi.org/10.1109/IJCSS.2011.73

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title = "Using feature selection to reduce the complexity in analyzing the injury severity of traffic accidents",

abstract = "When analyzing the traffic accidents in terms of predicting injury severity, past studies often use too many variables and thus lead to over fitting and complicate the interpretation of the analysis. By adopting feature selection technique, irrelevant and redundant features from a dataset will be filtered out such that high discrimination power and informative features will be provided. This paper selects twenty eight factors by adopting feature selection to analyze the injury severity of traffic accidents in Taiwan. The method facilitates to reduce the complexity of analyzing the injury severity of traffic accidents. The findings show that nineteen factors are classified into important; one is categorized as marginal; and five are grouped into unimportant.",

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Wei, JT, Wu, HH & Kou, KY 2011, Using feature selection to reduce the complexity in analyzing the injury severity of traffic accidents. in Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011., 5960374, Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011, pp. 329-333, 2011 International Joint Conference on Service Sciences, IJCSS 2011, Taipei, Taiwan, 11-05-25. https://doi.org/10.1109/IJCSS.2011.73

Using feature selection to reduce the complexity in analyzing the injury severity of traffic accidents. / Wei, Jo Ting; Wu, Hsin Hung; Kou, Kuang Yang.

Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011. 2011. p. 329-333 5960374 (Proceedings - 2011 International Joint Conference on Service Sciences, IJCSS 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Access to Document

10.1109/IJCSS.2011.73