Clustering Trend Predictions using Evolutionary k-means Algorithm for Automated Clustering
Published: 2013
Author(s) Name: Jyoti Lakhani, Dharmesh Harwani |
Author(s) Affiliation: Maharaja Ganga Singh University, Bikaner, Rajasthan, India
Locked
Subscribed
Available for All
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
View PDF