%0 Conference Proceedings
%T Decision Trees and Their Families in Imbalanced Pattern Recognition: Recognition with and without Rejection
%+ Warsaw University of Technology [Warsaw]
%+ University of Bialystok
%A Homenda, Wladyslaw
%A Lesinski, Wojciech
%Z Part 4: Data Analysis and Information Retrieval
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 13th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Ho Chi Minh City, Vietnam
%Y Khalid Saeed
%Y Václav Snášel
%I Springer
%3 Computer Information Systems and Industrial Management
%V LNCS-8838
%P 219-230
%8 2014-11-05
%D 2014
%R 10.1007/978-3-662-45237-0_22
%K pattern recognition
%K decision tree
%K bagging
%K random forest
%K optical music recognition
%K imbalanced data
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X Decision trees are considered to be among the best classifiers. In this work we use decision trees and its families to the problem of imbalanced data recognition. Considered are aspects of recognition without rejection and with rejection: it is assumed that all recognized elements belong to desired classes in the first case and that some of them are outside of such classes and are not known at classifier’s training stage. The facets of imbalanced data and recognition with rejection affect different real world problems. In this paper we discuss results of experiment of imbalanced data recognition on the case study of music notation symbols. Decision trees and three methods of joining decision trees (simple voting, bagging and random forest) are studied. These methods are used for recognition without and with rejection.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01405585/document
%2 https://inria.hal.science/hal-01405585/file/978-3-662-45237-0_22_Chapter.pdf
%L hal-01405585
%U https://inria.hal.science/hal-01405585
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-LNCS-8838
%~ IFIP-CISIM