arrow
Volume 2, Issue 3
A New Reduction Implementation Based on Concept

J. Info. Comput. Sci. , 2 (2007), pp. 223-227.

Export citation
  • Abstract
Rough set is one of the most useful data mining techniques. How to use rough set to extract rule is the basement of rough set’s application. This paper discuss an algorithm that be used in attribute reduction. To attribute reduction, generally method is based on discernibility matrix or its improvement. But this series methods usually get one reduction, can’t accommodate uncertain information reasoning. We provide a reduction algorithm, which based on reduction pruning. It can calculate all reductions, and suits any uncertain knowledge reasoning. For increase this algorithm’s effective, we present two theorems to make algorithm simplified. We calculate reduction through rough reduction (reduction pruning) and backward elimination two steps. The case illustrates we get the reduction effectively through this algorithm.
  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{JICS-2-223, author = {}, title = {A New Reduction Implementation Based on Concept}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {2}, number = {3}, pages = {223--227}, abstract = { Rough set is one of the most useful data mining techniques. How to use rough set to extract rule is the basement of rough set’s application. This paper discuss an algorithm that be used in attribute reduction. To attribute reduction, generally method is based on discernibility matrix or its improvement. But this series methods usually get one reduction, can’t accommodate uncertain information reasoning. We provide a reduction algorithm, which based on reduction pruning. It can calculate all reductions, and suits any uncertain knowledge reasoning. For increase this algorithm’s effective, we present two theorems to make algorithm simplified. We calculate reduction through rough reduction (reduction pruning) and backward elimination two steps. The case illustrates we get the reduction effectively through this algorithm. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22802.html} }
TY - JOUR T1 - A New Reduction Implementation Based on Concept AU - JO - Journal of Information and Computing Science VL - 3 SP - 223 EP - 227 PY - 2024 DA - 2024/01 SN - 2 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22802.html KW - rough set, reduction, pruning, backward elimination AB - Rough set is one of the most useful data mining techniques. How to use rough set to extract rule is the basement of rough set’s application. This paper discuss an algorithm that be used in attribute reduction. To attribute reduction, generally method is based on discernibility matrix or its improvement. But this series methods usually get one reduction, can’t accommodate uncertain information reasoning. We provide a reduction algorithm, which based on reduction pruning. It can calculate all reductions, and suits any uncertain knowledge reasoning. For increase this algorithm’s effective, we present two theorems to make algorithm simplified. We calculate reduction through rough reduction (reduction pruning) and backward elimination two steps. The case illustrates we get the reduction effectively through this algorithm.
. (2024). A New Reduction Implementation Based on Concept. Journal of Information and Computing Science. 2 (3). 223-227. doi:
Copy to clipboard
The citation has been copied to your clipboard