International Journal of Banking, Risk and Insurance

2013 | Volume 1 | Issue 2

Clustering Trend Predictions using Evolutionary k-means Algorithm for Automated Clustering

1. Jyoti Lakhani – Maharaja Ganga Singh University, Bikaner, Rajasthan, India

2. Dharmesh Harwani – Maharaja Ganga Singh University, Bikaner, Rajasthan, India

Received
14-Mar-2014 		Accepted
- 		Published
14-Mar-2014
Abstract
The paper proposed a method of hybridization of k-means algorithm and evolutionary programming. The blend of the two generates k number of clusters C = (c1, ..., ck) in the data space D = {x1, ..., xn}. These clusters will evolve in such a way that prediction of the upcoming trends of clusters in the application is possible. The proposed hybrid is named as evolutionary k-means clustering algorithm which is useful in generating and predicting clustering trends in an automated system.
Keywords Clustering, Data Mining, Evolutionary Programming, K-Means
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