DocumentCode :
2543486
Title :
The Detection of Breast Cancer Based on Dynamic Feature Selection with EM-Bayesian Ensemble Classifier
Author :
Fu, Qiang ; Feng, Jun ; Wang, Huiya
Author_Institution :
Sch. of Inf. Sci. & Technol., Northwest Univ., Xi´´an, China
fYear :
2009
fDate :
4-6 Nov. 2009
Firstpage :
1
Lastpage :
5
Abstract :
When solving the problem in computer assisted detection by the approach of pattern recognition, the lesion data always exhibited high-dimensional and inhomogeneous, which makes most of the traditional classifiers can not performance very well. In this paper, a novel approach based on the dynamic feature subset selection and the EM algorithm with Naive Bayesian classifier integration algorithm (DSFS+EMNB) is proposed. The experimental results demonstrated that this method significantly outperforms the other methods like SVM and other traditional classification methods in terms of average accuracy, as well as generality.
Keywords :
Bayes methods; cancer; expectation-maximisation algorithm; feature extraction; medical computing; pattern classification; support vector machines; EM-Bayesian ensemble classifier; SVM; breast cancer detection; computer assisted detection; dynamic feature subset selection; pattern recognition; Bayesian methods; Breast cancer; Cancer detection; Electronic mail; High performance computing; Information science; Mathematics; Pattern recognition; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4199-0
Type :
conf
DOI :
10.1109/CCPR.2009.5344127
Filename :
5344127
Link To Document :
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