Title :
Analyzing Feature Significance from Various Systems for Mass Diagnosis
Author :
Ping Zhang ; Kumar, Kuldeep
Author_Institution :
Bond University, Gold Coast, QLD 4229, Australia
fDate :
Nov. 28 2006-Dec. 1 2006
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;
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
DOI :
10.1109/CIMCA.2006.46
