http://www.cnr.it/ontology/cnr/individuo/prodotto/ID44167
Evaluation of feature subset selection, feature weighting, and prototype selection for biomedical applications (Articolo in rivista)
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- Evaluation of feature subset selection, feature weighting, and prototype selection for biomedical applications (Articolo in rivista) (literal)
- Anno
- 2008-01-01T00:00:00+01:00 (literal)
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- Little S.; Salvetti O.; Perner P. (literal)
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- In: ECCBR 2008 - Advances in Case-Based Reasoning, 9th European Conference (Trier, Germany, 1-4 September 2008). Proceedings, pp. 312 - 324. Klaus-Dieter Althoff, Ralph Bergmann, Mirjam Minor, Alexandre Hanft (eds.). (Lecture Notes in Computer Science, vol. 5239). Springer, 2008. (literal)
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Institute of Computer Vision and Applied Computer Sciences, Germany, CNR-ISTI, Pisa (literal)
- Titolo
- Evaluation of feature subset selection, feature weighting, and prototype selection for biomedical applications (literal)
- Abstract
- Many medical diagnosis applications are characterized by datasets that contain under-represented classes due to the fact that the disease appears more rarely than the normal case. In such a situation classifiers that generalize over the data such as decision trees and Naïve Bayesian 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 Naïve Bayesian. Finally, we give an outlook for further work. (literal)
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