원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.8 No.1
2015.02
pp.157-168
피인용수 : 0건 (자료제공 : 네이버학술정보)
목차
Abstract
1. Introduction
2. Basic Idea of Cluster Arithmetic
2.1 The Definition of Cluster
2.2 Similarity Metric Function
2.3 Criteriion Function
3. K-means Clustering Algorithm
3.1 Calculation Steps of K-means Algorithm
3.2 Clustering Algorithm of Automatic Gained Parameter Value k based on Maximized Distance
4. Simulation Experiments and Results Analysis
5. Conclusions
Acknowledgments
References
1. Introduction
2. Basic Idea of Cluster Arithmetic
2.1 The Definition of Cluster
2.2 Similarity Metric Function
2.3 Criteriion Function
3. K-means Clustering Algorithm
3.1 Calculation Steps of K-means Algorithm
3.2 Clustering Algorithm of Automatic Gained Parameter Value k based on Maximized Distance
4. Simulation Experiments and Results Analysis
5. Conclusions
Acknowledgments
References
저자정보
참고문헌
자료제공 : 네이버학술정보