Probability Measures for Prediction in Multi-table Infomation Systems

  • R. S. Milton
  • V. Uma Maheswari
  • Arul Siromoney
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)


Rough Set Theory is a mathematical tool to deal with vagueness and uncertainty. Rough Set Theory uses a single information table. Relational Learning is the learning from multiple relations or tables. This paper presents a new approach to the extension of Rough Set Theory to multiple relations or tables. The utility of this approach is shown in classification experiments in predictive toxicology.


Decision Table Decision Class Granular Computing Multiple Relation Link Attribute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • R. S. Milton
    • 1
  • V. Uma Maheswari
    • 2
  • Arul Siromoney
    • 2
  1. 1.Department of Computer ScienceMadras Christian CollegeChennaiIndia
  2. 2.Department of Computer Science and Engineering, College of EngineeringAnna UniversityChennaiIndia

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