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Computer Information Systems and Industrial Management 13th IFIP TC8 International Conference, CISIM 2014, Ho Chi Minh City, Vietnam, November 5-7, 2014 |
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Conference papers
Decision Trees and Their Families in Imbalanced Pattern Recognition: Recognition with and without Rejection
Abstract : 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.
Cited literature [16 references]
https://hal.inria.fr/hal-01405585
Contributor : Hal Ifip <>
Submitted on : Wednesday, November 30, 2016 - 10:58:12 AM
Last modification on : Thursday, December 1, 2016 - 1:04:16 AM
Document(s) archivé(s) le : Monday, March 27, 2017 - 7:50:23 AM
Contributor : Hal Ifip <>
Submitted on : Wednesday, November 30, 2016 - 10:58:12 AM
Last modification on : Thursday, December 1, 2016 - 1:04:16 AM
Document(s) archivé(s) le : Monday, March 27, 2017 - 7:50:23 AM
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