The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Improvements of K-modes Algorithm and ROCK Algorithm

K-모드 알고리즘과 ROCK 알고리즘의 개선

  • 김보화 (한국산업은행) ;
  • 김규성 (서울시립대학교 컴퓨터·통계학과)
  • Published : 2002.09.01
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Abstract

K-modes algorithm and ROCK(RObust Clustering using linKs) algorithm we useful clustering methods for large categorical data. In the paper, we investigate these algorithms and propose improved algorithms of them to correct their weakness. A simulation study shows that the proposed algorithms could increase the performance of data clustering.

K-모드(modes) 알고리즘과 락(ROCK) 알고리즘은 대규모 범주형 자료에 적용 가능한 데이터 군집화 방법이다. 이 논문에서는 두 알고리즘을 고찰하였으며, 두 알고리즘의 단점을 보완한 개선된 데이터 군집화 알고리즘을 제안하였다. 그리고 실제자료에 제안된 방법을 적용한 모의실험을 실시하여 제안된 방법이 데이터 군집화의 성능을 향상시킬 수 있음을 보였다.

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