Show simple item record

dc.contributor.authorGüvenir, H. A.en_US
dc.contributor.authorDemiröz, G.en_US
dc.contributor.authorİlter, N.en_US
dc.date.accessioned2015-07-28T11:56:37Z
dc.date.available2015-07-28T11:56:37Z
dc.date.issued1998en_US
dc.identifier.issn0933-3657
dc.identifier.urihttp://hdl.handle.net/11693/11003en_US
dc.description.abstractA new classification algorithm, called VFI5 (for Voting Feature Intervals), is developed and applied to problem of differential diagnosis of erythemato-squamous diseases. The domain contains records of patients with known diagnosis. Given a training set of such records, the VFI5 classifier learns how to differentiate a new case in the domain. VFI5 represents a concept in the form of feature intervals on each feature dimension separately. classification in the VFI5 algorithm is based on a real-valued voting. Each feature equally participates in the voting process and the class that receives the maximum amount of votes is declared to be the predicted class. The performance of the VFI5 classifier is evaluated empirically in terms of classification accuracy and running time. (C) 1998 Elsevier Science B.V. All rights reserved.en_US
dc.language.isoEnglishen_US
dc.source.titleArtificial Intelligence in Medicineen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/S0933-3657(98)00028-1en_US
dc.subjectMachine Learningen_US
dc.subjectDifferential Diagnosisen_US
dc.subjectErythemato-Squamousen_US
dc.subjectVoting Feature Intervalsen_US
dc.titleLearning differential diagnosis of erythemato-squamous diseases using voting feature intervalsen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage147en_US
dc.citation.epage165en_US
dc.citation.volumeNumber13en_US
dc.citation.issueNumber3en_US
dc.identifier.doi10.1016/S0933-3657(98)00028-1en_US
dc.publisherElsevieren_US
dc.identifier.eissn1873-2860


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record