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The number of accidents and health diseases which are increasing at an alarming rate are resulting in a huge increase in the demand for blood. There is a necessity for the organized analysis of the blood donor database or blood banks repositories. Clustering analysis is one of the data mining applications and Kmeans clustering algorithm is the fundamental algorithm for modern clustering techniques. Kmeans clustering algorithm is traditional approach and iterative algorithm. At every iteration, it attempts to find the distance from the centroid of each cluster to each and every data point. This paper gives the improvement to the original kmeans algorithm by improving the initial centroids with distribution of data. Results and discussions show that improved Kmeans algorithm produces accurate clusters in less computation time to find the donors information
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