A hybrid clustering algorithm for data mining
Databases
2012-05-25 v1 Machine Learning
Abstract
Data clustering is a process of arranging similar data into groups. A clustering algorithm partitions a data set into several groups such that the similarity within a group is better than among groups. In this paper a hybrid clustering algorithm based on K-mean and K-harmonic mean (KHM) is described. The proposed algorithm is tested on five different datasets. The research is focused on fast and accurate clustering. Its performance is compared with the traditional K-means & KHM algorithm. The result obtained from proposed hybrid algorithm is much better than the traditional K-mean & KHM algorithm.
Keywords
Cite
@article{arxiv.1205.5353,
title = {A hybrid clustering algorithm for data mining},
author = {Ravindra Jain},
journal= {arXiv preprint arXiv:1205.5353},
year = {2012}
}