dos Santos, T.R.L. and Zarate, L.E. (2015) Categorical Data Clustering: What Similarity Measure to Recommend? Expert Systems with Applications, 42, 1247-1260.

has been cited by the following article:

• TITLE: Clustering Categorical Data Based on Within-Cluster Relative Mean Difference

  AUTHORS: Jinxia Su, Chunjing Su

  KEYWORDS: Clustering, Categorical Variable, Distinctive Attribute, Pooled Within-Cluster Mean Relative Difference, Hamming Distance

  JOURNAL NAME: Open Journal of Statistics, Vol.7 No.2, April 20, 2017

  ABSTRACT: The clustering on categorical variables has received intensive attention. In dataset with categorical features, some features show the superior performance on clustering procedure. In this paper, we propose a simple method to find such distinctive features by comparing pooled within-cluster mean relative difference and then partition the data upon such features and give subspace of the subgroups. The applications on zoo data and soybean data illustrate the performance of the proposed method.