Multidimensional Scaling Using the Pseudo-Points Based on Partition Method

분할법에 의한 가상점을 활용한 다차원척도법

Shin, Sang Min;Kim, Eun-Seong;Choi, Yong-Seok

  • Received : 2015.10.12
  • Accepted : 2015.12.14
  • Published : 2015.12.31


Multidimensional scaling (MDS) is a graphical technique of multivariate analysis to display dissimilarities among individuals into low-dimensional space. We often have two kinds of MDS which are metric MDS and non-metric MDS. Metric MDS can be applied to quantitative data; however, we need additional information about variables because it only shows relationships among individuals. Gower (1992) proposed a method that can represent variable information using trajectories of the pseudo-points for quantitative variables on the metric MDS space. We will call his method a 'replacement method'. However, the trajectory can not be represented even though metric MDS can be applied to binary data when we apply his method to binary data. Therefore, we propose a method to represent information of binary variables using pseudo-points called a 'partition method'. The proposed method partitions pseudo-points, accounting both the rate of zeroes and ones. Our metric MDS using the proposed partition method can show the relationship between individuals and variables for binary data.


multidimensional scaling;pseudo-points;replacement method;partition method


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