Context Out Classifier
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Date
2018-06-01
Authors
Hrebik, Radek
Kukal, Jaromir
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Automation and Computer Science, Brno University of Technology
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Abstract
Novel context out learning approach is discussed as possibility of using simple classifiers which is background of hidden class system. There are two ways how to perform final classification. Having a lot of hidden classes we can build their unions using binary optimization task. Resulting system has the best possible sensitivity over all output classes. Another way is to perform second level linear classification as referential approach. The presented techniques are demonstrated on traditional iris flower task.
Description
Citation
Mendel. 2018 vol. 24, č. 1, s. 101-106. ISSN 1803-3814
https://mendel-journal.org/index.php/mendel/article/view/29
https://mendel-journal.org/index.php/mendel/article/view/29
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en