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Mine Blood Donors Information through Improved K Means Clustering


Paridhi Pachori , College of Engineering, Bharati Vidyapeeth University, Pune


Alzheimer Disease, Mine Blood Donors Information, Clustering Algorithm


The number of accidents and health diseases increasing at an alarming rate has resulted 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 K-means clustering algorithm is the fundamental algorithm and traditional approach for modern clustering techniques. The K-means clustering is an iterative algorithm which attempts to find the distance from the centroid of each cluster to each and every data point at every iteration. This paper gives the improvement to the original k-means algorithm by improving the initial centroids with distribution of data. Results and discussions show that improved K-means algorithm produces accurate clusters in less computation time to find the donors information.

Other Details

Paper ID: NCILP016
Published in: Conference 1 : NCIL 2015
Publication Date: 16/10/2015
Page(s): 65-69

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