Title :
A feature selection approach to concept acquisition
Author :
Moraes, Ian ; Cios, Krzysztof J.
Author_Institution :
Dept. of Electr. Eng., Toledo Univ., OH, USA
Abstract :
A concept acquisition algorithm (ALFS) based on the selection of so-called best features was developed to learn decision rules to recognize examples from different subsets of a training data set. The features which best represent and differentiate a particular subset from all other subsets are used to form the rules. A knowledge base for a diagnostic expert system is produced using the rules. The results obtained by applying ALFS to two established learning data sets from the domains of breast cancer and lymphography are reported
Keywords :
expert systems; medical diagnostic computing; best features selection; breast cancer; concept acquisition; concept acquisition algorithm; decision rules learning; diagnostic expert system; feature selection approach; knowledge base; lymphography; training data set; Breast cancer; Decision making; Diagnostic expert systems; Humans; Hydrogen; Knowledge acquisition; Partitioning algorithms; Training data;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.96469
