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This paper presents the analysis of K-means and K-Medians clustering algorithm in detecting outliers. Clustering is generally used in pattern recognition where if a user wants to search for some particular pattern, clustering reduces the searching load. The k-means clustering and k-medians clustering algorithm's performance in detecting outliers are analyzed here. K-means clustering clusters the similar data with the help of the mean value and squared error criterion. K-medians is similar to k-means algorithm but median values are calculated there. Outliers are the one different from norm. If they are not properly detected and handled, they clustering will be affected in a great manner.
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