Data Clustering

Chapter 18

A Survey of Uncertain Data Clustering Algorithms

Charu C. Aggarwal

IBM T. J. Watson Research Center Yorktown Heights, [e-mail]

18.1 Introduction

Many data sets which are collected often have uncertainty built into them. In many cases, the underlying uncertainty can be easily measured and collected. When this is the case, it is possible to use the uncertainty in order to improve the results of data mining algorithms. This is because the uncertainty provides a probabilistic measure of the relative importance of different attributes in data mining algorithms. The use of such information can enhance the effectiveness of data mining algorithms, because the uncertainty provides a guidance in the use of different attributes during ...