Reason-A Technical Journal (Formerly Reason-A Technical Magazine)

Open Access Open Access  Restricted Access Subscription Access

Rough Set: A Case Study on Technical Teachers' Training Data


Affiliations
1 National Institute of Technical Teachers’ Training & Research, Kolkata, India
 

This paper presents the theory of rough sets as a mathematical model of vague or inexact data. As well as it's application as a data mining tool for rule generation, out of large data. The domain of data has been taken from the training data of National Institute of Technical Teachers' Training&Research, Kolkata. ROSETTA, a rough set theoretic application tool developed at Warsaw University, Poland, has been used for the purpose. The rules generated through experiment reveal interesting knowledge hidden in the un-organized data of the target domain.

Keywords

Indiscernibility, Boundary Regions, Reducts, ROSETTA, Rule Extraction.
User
Notifications
Font Size


  • Roy, S. and Chakraborty, U., Introduction to Soft Computing: Neuro-Fuzzy and Genetic Algorithms, Pearson, 2013.

  • Slimani T., Application of Rough Set Theory in Data Mining, International Journal of Computer Science & Network Solutions, Vol. 1, No.3, pp.1-10, 2013.

  • Pawlak, Z., Rough Sets, International Journal of Computer & Information Sciences, Vol. 11, No.5, pp.341-356, 1982.

  • Grzymala-Busse, J.W., Rough Set Theory with Applications to Data Mining, Chapter-Real World Applications of Computational Intelligence, Vol. 179, Studies in Fuzziness and Soft Computing, pp.221-244, 2005.

  • Komorowski, J., hrn, A. and Skowron, A., The ROSETTA Rough Set Software System.

  • Hvidsten T.R., A Tutorial-Based Guide to the ROSETTA System: A Rough Set Toolkit for Analysis of Data, May 2006.


Abstract Views: 544

PDF Views: 162




  • Rough Set: A Case Study on Technical Teachers' Training Data

Abstract Views: 544  |  PDF Views: 162

Authors

Sukanta Ghosal
National Institute of Technical Teachers’ Training & Research, Kolkata, India
Samir Roy
National Institute of Technical Teachers’ Training & Research, Kolkata, India

Abstract


This paper presents the theory of rough sets as a mathematical model of vague or inexact data. As well as it's application as a data mining tool for rule generation, out of large data. The domain of data has been taken from the training data of National Institute of Technical Teachers' Training&Research, Kolkata. ROSETTA, a rough set theoretic application tool developed at Warsaw University, Poland, has been used for the purpose. The rules generated through experiment reveal interesting knowledge hidden in the un-organized data of the target domain.

Keywords


Indiscernibility, Boundary Regions, Reducts, ROSETTA, Rule Extraction.

References





DOI: https://doi.org/10.21843/reas%2F2015%2F75-82%2F108343