Research and Discussion on the Novel Big Data Clustering Algorithm based on Probability Theory and Nash Game Theory
Authors
Liang Haijun
Corresponding Author
Liang Haijun
Available Online September 2015.
- DOI
- 10.2991/iemb-15.2015.206How to use a DOI?
- Keywords
- Data Clustering; Probability Theory; Nash Game Theory; Experimental Analysis.
- Abstract
In this paper, we conduct research on the novel big data clustering algorithm based on probability theory and Nash game theory. Clustering algorithm is an effective method of data analysis, clustering algorithm is without any prior information of data clustering analysis of data and this kind of algorithm is also known as unsupervised learning methods. The Nash game theory and probability enhance the performance of the traditional clustering algorithm. The experiment result proves the feasibility of the combination. We set the schedule and prospect in the final part.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Liang Haijun PY - 2015/09 DA - 2015/09 TI - Research and Discussion on the Novel Big Data Clustering Algorithm based on Probability Theory and Nash Game Theory BT - Proceedings of the 2015 Conference on Informatization in Education, Management and Business PB - Atlantis Press SP - 1008 EP - 1012 SN - 2352-5398 UR - https://doi.org/10.2991/iemb-15.2015.206 DO - 10.2991/iemb-15.2015.206 ID - Haijun2015/09 ER -