Earticle

초록

영어

For multi-relational data mining, efficiency is always a focus of research. The main bottleneck to improve the efficiency of the algorithm is hypothesis space. This paper presents the improved multi-relational decision tree algorithm, MRDTL-2, whose efficiency is improved. First, the tuple ID propogation technology is applied to the multi-relational decision tree algorithm. Secondly, under user’s guide, when a data item is greater than the transmitting threshold, set the null relationship Ra. And transmit the primary key, the background attributes, the class label to Ra, then Ra involves in other multi-relational decision tree algorithms instead of the background relations. Finally, the paper has carried on the experiments to verify the improved multi-relational decision tree algorithm MRDTL-2.

목차

Abstract
 1. Introduction
 2. The Thought of the Improved Algorithm
 3. The Concrete Implementation Process of MRDTL-2 Algorithm
  3.1. Basic Theory
  3.2. The Implementation of MRDTL-2 Algorithm
 4. Experiment Analysis
  4.1. The Experimental Running Environment
  4.2. The Experimental Data
  4.3. The Experiment Process and Results
  4.4. Experiment Analysis
 5. Conclusion
 References

키워드

저자

• Juan Li [ School of Computer Engineering, Jinling Institute of Technology, Nanjing, 211169, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605