The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A study on high dimensional large-scale data visualization

고차원 대용량 자료의 시각화에 대한 고찰

  • 이은경 (이화여자대학교 통계학과) ;
  • 황나영 (이화여자대학교 통계학과) ;
  • 이윤동 (서강대학교 경영학부)
  • Received : 2016.08.31
  • Accepted : 2016.10.02
  • Published : 2016.10.31
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Abstract

In this paper, we discuss various methods to visualize high dimensional large-scale data and review some issues associated with visualizing this type of data. High-dimensional data can be presented in a 2-dimensional space with a few selected important variables. We can visualize more variables with various aesthetic attributes in graphics or use the projection pursuit method to find an interesting low-dimensional view. For large-scale data, we discuss jittering and alpha blending methods that solve any problem with overlapping points. We also review the R package tabplot, scagnostics, and other R packages for interactive web application with visualization.

본 논문에서는 고차원 대용량 자료의 시각화에서 발생할 수 있는 문제점들을 살펴보고 이에 대하여 개발된 방법들에 대하여 논의하였다. 고차원 자료의 경우 2차원 공간상에 표현하기 위하여 중요 변수를 선택해야하며 다양한 시각적 표현 속성과 다면화 방법을 이용하여 좀 더 많은 변수들을 표현할 수 있었다. 또한 관심있는 뷰를 보이는 낮은 차원을 찾는 사영추정방법을 이용할 수 있다. 대용량 자료에서는 점들이 겹쳐지는 문제점을 흩트림과 알파 블렌딩 등을 이용하여 해결할 수 있었다. 또한 고차원 대용량 자료의 탐색을 위하여 개발된 R 패키지인 tabplot과 scagnostics, 그리고 대화형 웹 그래프를 위한 다양한 형태의 R 패키지들을 살펴보았다.

Keywords

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