We examine methods for clustering in high dimensions. In the first part of the paper, we perform an experimental comparison between three batch clustering algorithms: the Expectat...
Clustering accuracy of partitional clustering algorithm for categorical data primarily depends upon the choice of initial data points (modes) to instigate the clustering process. ...
: The issue of determining "the right number of clusters" in K-Means has attracted considerable interest, especially in the recent years. Cluster intermix appears to be a...
: In the paper nine different approaches to missing attribute values are presented and compared. Ten input data files were used to investigate the performance of the nine methods t...
Bayesian Information Criterion (BIC) is a promising method for detecting the number of clusters. It is often used in model-based clustering in which a decisive first local maximum ...