DocumentCode
3099893
Title
Analyzing Feature Significance from Various Systems for Mass Diagnosis
Author
Ping Zhang ; Kumar, Kuldeep
Author_Institution
Bond University, Gold Coast, QLD 4229, Australia
fYear
2006
fDate
Nov. 28 2006-Dec. 1 2006
Firstpage
141
Lastpage
141
Abstract
This paper compares a few classification models for mass classification and analyzes the feature significance for mass classification using various models. It involves a few algorithms for feature selection and also analyzes the individual feature significance. The comparison of classification models is based on the same datasets for mass diagnosis.
Keywords
feature extraction; image classification; medical diagnostic computing; classification models; feature selection; feature significance; mass classification; mass diagnosis; Australia; Cancer; Computational intelligence; Feature extraction; Humans; Image segmentation; Mammography; Neural networks; Spatial databases; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
0-7695-2731-0
Type
conf
DOI
10.1109/CIMCA.2006.46
Filename
4052770
Link To Document