Earticle

초록

영어

After analysis the importance of continuous attributes in the C5.0 algorithm processing, and consider the shortcomings of discretization method of C5 algorithm, this paper proposes a new method based on Rough set theory- information entropy- discernible matrix discretization (RSIEDM). The method uses rough, information entropy and Discernible matrix that can be more reasonable and more accurately to continuously attribute discretization, and making created decision tree have better accuracy. In the application of optimization of lightning disaster statistics and evaluation result of lightning disaster, the algorithm which has obtained a better effect.

목차

Abstract
 1. Introduction
 2. Decision Tree Classification Algorithm
  2.1 Create Decision Tree
  2.2 Discretize the continuous valued attribute
 3. Design Discretized Research based on Rough Set-information Entropy-Discernible Matrix
  3.1 Algorithm of initial breakpoints set
  3.2 The information entropy of rough set attributes discretization method
  3.3 Attribute reduction of discernibility matrix
 4. Body Area Sensor Network
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Shuonan Hou [ College of Information Science and Engineering, Northeastern University, ShenYang 110819, Liaoning, China ]
• Rongtao Hou [ School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China ]
• Xinming Shi [ School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China ]
• Jun Wang [ School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China ]
• Chengshang Yuan [ School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605