DocumentCode
1687790
Title
Learning rules by integer linear programming
Author
Liu, Ning ; Cios, Krzysztof J.
Author_Institution
Toledo Univ., OH, USA
fYear
1992
Firstpage
246
Abstract
In this work, an inductive machine learning algorithm called CLILP2, which uses integer linear programming to generate multiple decision rules, is applied to two types of medical data. One is concerned with heart data to recognize coronary artery stenosis from the left ventricle scintigraphic images, and the other data set represents different types of cancer, namely, breast cancer, lymphography and a primary tumor
Keywords
image recognition; integer programming; learning (artificial intelligence); linear programming; medical image processing; CLILP2; artificial intelligence; biomedical computing; cancer; coronary artery stenosis; heart; image recognition; inductive machine learning algorithm; integer linear programming; left ventricle scintigraphic images; lymphography; medical data; multiple decision rules; primary tumor; Biomedical imaging; Colored noise; Decision trees; Heart; Induction generators; Integer linear programming; Machine learning algorithms; Shape; Testing; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, 1992., Proceedings of the IEEE International Symposium on
Conference_Location
Xian
Print_ISBN
0-7803-0042-4
Type
conf
DOI
10.1109/ISIE.1992.279577
Filename
279577
Link To Document