Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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A polychotomous regression model with tensor product splines and direct sums

연속형의 텐서곱과 범주형의 직합을 사용한 다항 로지스틱 회귀모형

  • Sim, Songyong (Department of Finance & Information Statistics, Hallym University) ;
  • Kang, Heemo (Department of Finance & Information Statistics, Hallym University)
  • 심송용 (한림대학교 금융정보통계학과) ;
  • 강희모 (한림대학교 금융정보통계학과)
  • Received : 2013.09.30
  • Accepted : 2013.11.11
  • Published : 2014.01.31
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Abstract

In this paper, we propose a polychotomous regression model when independent variables include both categorical and numerical variables. For categorical independent variables, we use direct sums, and tensor product splines are used for continuous independent variables. We use BIC for varible selections criterior. We implemented the algorithm and apply the algorithm to real data. The use of direct sums and tensor products outperformed the usual multinomial logistic regression model.

다항 로지스틱 회귀모형의 설명변수가 연속형과 범주형을 모두 포함할 때 범주형 설명변수는 직합을 적용하고 연속형 설명변수는 텐서곱을 적용하는 모형을 제안한다. 변수선택의 기준으로 BIC를 사용하고, 제안된 모형의 알고리즘을 구현하였다. 구현된 알고리즘을 실제 자료에 적용하여 기존의 방법과 비교하여 제안된 모형이 더 좋은 분류율을 보임을 확인하였다.

Keywords

References

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