Date Added: Jul 2011
The power of modern computing technology makes data gathering and storage easier. This leads to create new range of problems and challenges for data analysis. In this paper approach based on clustering techniques for outlier detection is presented. At first EM-Cluster algorithm is performed to identify the missing values through which small clusters are formed. Then univariate outlier detection method is applied to identify outliers. The proposed approach gave effective results within optimum time and space when applied to synthetic data set.