Classification with rejection: concepts and evaluations

Władysław Homenda , Marcin Luckner , Witold Pedrycz


Standard classification process allocates all processed elements to given classes. Such type of classification assumes that there is are only native and no foreign elements, i.e. all processed elements are included in given classes. The quality of standard classification can be measured by two factors: numbers of correctly and incorrectly classified elements, called True Positives and False Positives. Admitting foreign elements in standard classification process increases False Positives and, in this way, deteriorates quality of classification. In this context, it is desired to reject foreign elements, i.e. to not assign them to any of given classes. Rejecting foreign elements will reduce the number of False Positives, but can also reject native elements reducing True Positives as side effect. Therefore, it is important to build well designed rejection, which will reject significant part of foreigners and only few natives. In this paper, evaluations of classification with rejection concepts are presented. Three main models: a classification without rejection, a classification with rejection, and a classification with reclassification are presented. The concepts are illustrated by flexible ensembles of binary classifiers with evaluations of each model. The proposed models can be used, in particular, as classifiers working with noised data, where recognized input is not limited to elements of known classes.
Author Władysław Homenda (FMIS / DACSCM)
Władysław Homenda,,
- Department of Applied Computer Science and Computation Methods
, Marcin Luckner (FMIS / DACSCM)
Marcin Luckner,,
- Department of Applied Computer Science and Computation Methods
, Witold Pedrycz - [Systems Research Institute of the Polish Academy of Sciences]
Witold Pedrycz,,
Publication size in sheets0.6
Book Skulimowski Andrzej M. J., Kacprzyk Janusz (eds.): Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions, Advances in Intelligent Systems and Computing, vol. 364, no. Part V, 2016, Springer International Publishing, ISBN 978-3-319-19089-1, 566 p., DOI:10.1007/978-3-319-19090-7
Keywords in EnglishRejection rule, Binary classifiers ensemble, Reclassification
Abstract in PolishW standardowych metodach klasyfikacji zakłada się, że przetwarzane elementy należą do znanych klas. W zastosowaniach praktycznych często występują elementy obce spoza znanych klas. Klasyfikatory skonstruowane według standardowych metod klasyfikują obce elementy do danych klas. Każdy tego typu przypadek generuje błąd. Niniejsza praca poświęcona jest analizie klasyfikacji z odrzucaniem elementów obcych. Zaproponowane zostały metody analizy prowadzące do identyfikacji elementów obcych oraz miary oceny jakości klasyfikacji z odrzucaniem.
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 26-01-2020, BookChapterSeriesAndMatConfByConferenceseries
Ministerial score (2013-2016) = 15.0, 26-01-2020, BookChapterSeriesAndMatConfByConferenceseries
Publication indicators WoS Citations = 2; Scopus Citations = 2
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