Classification ensemble for mammograms using Ant-Miner

Author

Roselin, R. ; Thangavel, K.

Author_Institution

Comput. Sci., Sri Sarda Coll. for Women (Autonomous), Salem, India

fYear

2010

fDate

29-31 July 2010

Firstpage

1

Lastpage

6

Abstract

This paper proposes a new classification method based on association rule mining. This association rule-based classifier is experimented on a real dataset; a database of medical images from MIAS database. The proposed system employs Ant-Miner metaheuristic algorithm for extracting knowledge in the form of decision rules using texture features extracted with the help of co-occurrence matrices. These rules are used to predict unseen mammogram. The experimental results show that the method performs with greater accuracy.

Keywords

cancer; data mining; feature extraction; image classification; mammography; matrix algebra; visual databases; MIAS database; ant-miner metaheuristic algorithm; association rule mining; association rule-based classifier; classification ensemble; cooccurrence matrices; decision rules; knowledge extraction; mammograms; texture features extraction; Accuracy; Cancer; Classification algorithms; Data mining; Equations; Feature extraction; Prediction algorithms; Ant-Miner; Data mining; GLCM Matrix; Mammogram; Metaheuristic;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing Communication and Networking Technologies (ICCCNT), 2010 International Conference on

Conference_Location

Karur

Print_ISBN

978-1-4244-6591-0

Type

conf

DOI

10.1109/ICCCNT.2010.5592607

Filename

5592607