Multi Filtration Feature Selection (MFFS) to improve discriminatory ability in clinical data set

Multi Filtration Feature Selection (MFFS) to improve discriminatory ability in clinical data set

Selection of optimal features is an important area of research in medical data mining systems. In this paper we introduce an efficient four-stage procedure – feature extraction, feature subset selection, feature ranking and classification, called as Multi-Filtration Feature Selection (MFFS), for an...

Full description

Bibliographic Details
Main Authors: S. Sasikala, S. Appavu alias Balamurugan, S. Geetha
Format: Article
Language:English
Published: Emerald Publishing 2016-07-01
Series:Applied Computing and Informatics
Subjects:
Medical data mining
Biomedical classification
Variance coverage factor
Principal Component Analysis
Multi Filtration Feature Selection
Online Access:http://www.sciencedirect.com/science/article/pii/S2210832714000088

Internet

http://www.sciencedirect.com/science/article/pii/S2210832714000088

Similar Items