Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)
- Volume 19 Issue 37
- /
- Pages.41-51
- /
- 1996
- /
- 2005-0461(pISSN)
- /
- 2287-7975(eISSN)
A Study on Performance Evaluation of Clustering Algorithms using Neural and Statistical Method
신경망 및 통계적 방법에 의한 클러스터링 성능평가
Abstract
This paper evaluates the clustering performance of a neural network and a statistical method. Algorithms which are used in this paper are the GLVQ(Generalized Learning vector Quantization) for a neural method and the k-means algorithm fer a statistical clustering method. For comparison of two methods, we calculate the Rand's c statistics. As a result, the mean of c value obtained with the GLVQ is higher than that obtained with the k-means algorithm, while standard deviation of c value is lower. Experimental data sets were the Fisher's IRIS data and patterns extracted from handwritten numerals.
Keywords