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Using Rough Set Theory for Detecting the Interaction Terms in a Generalized Logit Model

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Rough Sets and Current Trends in Computing (RSCTC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3066))

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Abstract

Although logit model has been a popular statistical tool for classification problems it is hard to determine interaction terms in the logit model because of the NP-hard problem in searching all sample space. In this paper, we provide another viewpoint to consider interaction effects based on information granulation. We reduce the sample space of interaction effects using decision rules in rough set theory, and then use the procedure of stepwise selection method is used to select the significant interaction effects. Based on our results, the interaction terms are significant and the logit model with interaction terms performs better than other two models.

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Author information

Authors and Affiliations

  1. Institute of Information Management, No. 1, Sec. 4, Roosevelt Rd, Taipei, 106, Taiwan, R.O.C.

    Chorng-Shyong Ong & Jih-Jeng Huang

  2. Institute of Technology Management, 1001 Ta-Hsueh Road, Hsinchu, 300, Taiwan, ROC

    Gwo-Hshiung Tzeng

Authors
  1. Chorng-Shyong Ong
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  2. Jih-Jeng Huang
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  3. Gwo-Hshiung Tzeng
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Editor information

Editors and Affiliations

  1. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

  2. Systems Research Institute, Polish Academy of Sciences, 01-447, Warsaw, Poland

    Roman Słowiński

  3. The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden

    Jan Komorowski

  4. Institute of Computer Science, Polish Academy of Sciences, 01–237, Warsaw, Poland

    Jerzy W. Grzymała-Busse

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© 2004 Springer-Verlag Berlin Heidelberg

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Ong, CS., Huang, JJ., Tzeng, GH. (2004). Using Rough Set Theory for Detecting the Interaction Terms in a Generalized Logit Model. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_77

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  • DOI: https://doi.org/10.1007/978-3-540-25929-9_77

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22117-3

  • Online ISBN: 978-3-540-25929-9

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