Research Area:  Data Mining

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:  
clustering algorithm
data mining
K-mean
K-harmonic mean

Author(s) Name:  Ravindra Jain

Publisher name:  arXiv:1205.5353

DOI:  10.48550/arXiv.1205.5353

Volume Information:  

Paper Link:   https://arxiv.org/abs/1205.5353