Title :
Case based reasoning based on fuzzy rough set
Author :
Li, Xingyi ; Li, Xueling ; Shi, Huaji
Author_Institution :
Sch. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., Zhenjiang, China
Abstract :
This paper presents a new attribute significance measurement method based on the viewpoint of information theory of Fuzzy Rough Set. The method does not need to discretize continuous attributes included in cases, which can effectively reduce information loss, and it is suitable for the cases which contain both discrete and continuous attributes. Then it proposes a heuristic algorithm based on the new attribute significance for attribute reduction and weight distribution, and combines with the Nearest Neighbour (NN) method in case retrieve process. Finally, an example shows that this method improves accuracy and universality of the case retrieval.
Keywords :
case-based reasoning; fuzzy set theory; rough set theory; attribute reduction; case based reasoning; continuous attribute; discrete attribute; fuzzy rough set; heuristic algorithm; information theory; nearest neighbour method; weight distribution; Algorithm design and analysis; Artificial neural networks; Cognition; Hazards; Heuristic algorithms; Information entropy; Weather forecasting; attribute significant; case-based reasoning; fuzzy rough set; weight distribution;
Conference_Titel :
Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-6927-7
DOI :
10.1109/ICIFE.2010.5609472