K+ Means : An Enhancement Over K-Means Clustering Algorithm
Machine Learning
2017-06-23 v2
Abstract
K-means (MacQueen, 1967) [1] is one of the simplest unsupervised learning algorithms that solve the well-known clustering problem. The procedure follows a simple and easy way to classify a given data set to a predefined, say K number of clusters. Determination of K is a difficult job and it is not known that which value of K can partition the objects as per our intuition. To overcome this problem we proposed K+ Means algorithm. This algorithm is an enhancement over K-Means algorithm.
Cite
@article{arxiv.1706.02949,
title = {K+ Means : An Enhancement Over K-Means Clustering Algorithm},
author = {Srikanta Kolay and Kumar Sankar Ray and Abhoy Chand Mondal},
journal= {arXiv preprint arXiv:1706.02949},
year = {2017}
}
Comments
Authors: Co-author's name added Section 3: Step (a) and (b) of K+Means algorithm are merged for simplicity. Section 3.1: K+ Means algorithm complexity rectified. Section 4.3: Figure-7 and Figure-8 modified for clarity