Title :
Learning rules by integer linear programming
Author :
Liu, Ning ; Cios, Krzysztof J.
Author_Institution :
Toledo Univ., OH, USA
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;
Conference_Titel :
Industrial Electronics, 1992., Proceedings of the IEEE International Symposium on
Conference_Location :
Xian
Print_ISBN :
0-7803-0042-4
DOI :
10.1109/ISIE.1992.279577
