Bayesian Network for Data Mining
DOI:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest. It is a natural way to express the causal information, and to discover the hidden patterns among the data. Learning of Bayesian network is to find out a network model that best represents the dependent relationships of the variables in a database, that is, given sample D and prior knowledge ζ, to find a Bayesian network S that fits the maximum posterior probability p(sh|D,ζ). In this paper, the learning process of the network is strictly derived, and a case study is presented to indicate the applications of Bayesian network in data mining.

    Reference
    Related
    Cited by
Get Citation

慕春棣,戴剑彬,叶俊.用于数据挖掘的贝叶斯网络.软件学报,2000,11(5):660-666

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:March 15,1999
  • Revised:June 07,1999
  • Adopted:
  • Online:
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063