Earticle

초록

영어

This paper introduces a very important classification aspect for the analysis of huge amount of data stored in databases and other repositories. Numerous classification models are available in the literature, to predict the class of objects whose class level is unknown. Literature reveals that most of the available models are not capable in handling imperfect data. In view of this, present paper proposes a new rough set based classification model to derive the classification (IF-THEN) rules. Furthermore, developed model has been applied to handle bank-loan applications database as either safe, unsafe or risky. However, proposed model can also be used for the analysis of data from other domains.

목차

Abstract
 1. Introduction
 2. Basic Concept of Rough Set Theory:-
  2.1. Information System
  2.2. Indiscrenibility Relation
  2.3. Lower and Upper Approximations
  2.4. Accuracy of Approximation
  2.4. Core and Reduct of Attributes
 3. Proposed Rough set based Classification Algorithm
 4. Experimental Analysis:
 5. Conclusion
 References

키워드

저자

• Vinod Rampure [ Department of CSE & IT, Madhav Institute of Technology and Science, Gwalior (M.P), India ]
• Akhilesh Tiwari [ Department of CSE & IT, Madhav Institute of Technology and Science, Gwalior (M.P), India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605