A Comparative Study of Clustering Algorithms for Mixed Datasets

Clustering groups, a set of elements in a manner that elements in the same categoryhave more common characteristics (based on a given set of attributes) among themthan to elements in other categories. Each group is called a cluster. Clustering is used in many areas: sensor networks, social networks, health, business and other applications. There are many different clustering algorithms with different parameters. The appropriate clustering algorithm and parameter settings depend on data set and the problem being solved. Some work only on numerical data and other on mixed data. Our aim is to do a comparative study of these algorithms.