Istituto di Scienza e Tecnologie dell'Informazione     
Little S., Colantonio S., Salvetti O., Perner P. Evaluation of feature subset selection, feature weighting, and prototype selection for biomedical applications. In: Journal of Software Engineering and Applications, vol. 3 (1) pp. 39 - 49. Knowledge Research Publishing Inc, 2010.
Many medical diagnosis applications are characterized by datasets that contain under-represented classes due to the fact that the disease is much rarer than the normal case. In such a situation classifiers such as decision trees and Na´ve Bayesian that generalize over the data are not the proper choice as classification methods. Case-based classifiers that can work on the samples seen so far are more appropriate for such a task. We propose to calculate the contingency table and class specific evaluation measures despite the overall accuracy for evaluation purposes of classifiers for these specific data characteristics. We evaluate the different options of our case-based classifier and compare the performance to decision trees and Na´ve Bayesian. Finally, we give an outlook for further work.
URL: http://www.scirp.org/journal/home.aspx?IssueID=201&JournalID=45&paperID=1244
DOI: 10.4236/jsea.2010.31005
Subject Feature Subset Selection
Prototype Selection
Prototype-Based Classification
Case-based Reasoning in Health
I.2.6 Learning
I.5.2 Design Methodology
J.3 Life and Medical Sciences

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