Back to Search Start Over

OSDM: Optimized Shape Distribution Method.

Authors :
Li, Xue
Zaïane, Osmar R.
Li, Zhanhuai
Sami, Ashkan
Nagatomi, Ryoichi
Takahashi, Makoto
Tokuyama, Takeshi
Source :
Advanced Data Mining & Applications (9783540370253); 2006, p1057-1064, 8p
Publication Year :
2006

Abstract

Comprehensibility is vital in results of medical data mining systems since doctors simply require it. Another important issue specific to some data sets, like Fitness, is their uniform distribution due to tile analysis that was performed on them. In this paper, we propose a novel data mining tool named OSDM (Optimized Shape Distribution Method) to give a comprehensive view of correlations of attributes in cases of uneven frequency distribution among different values of symptoms. We apply OSDM to explore the relationship of the Fitness data and symptoms in medical test dataset for which popular data mining methods fail to give an appropriate output to help doctors decisions. In our experiment, OSDM found several useful relationships. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540370253
Database :
Complementary Index
Journal :
Advanced Data Mining & Applications (9783540370253)
Publication Type :
Book
Accession number :
32864363
Full Text :
https://doi.org/10.1007/11811305_115