A generalised label noise model for classification
Learning from labelled data is becoming more and more challenging due to inherent imperfection of training labels. In this paper, we propose a new, generalised label noise model which is able to withstand the negative effect of both random noise and a wide range of non-random label noises. Empirical...
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th-cmuir.6653943832-543562018-09-04T10:12:21Z A generalised label noise model for classification Jakramate Bootkrajang Computer Science Learning from labelled data is becoming more and more challenging due to inherent imperfection of training labels. In this paper, we propose a new, generalised label noise model which is able to withstand the negative effect of both random noise and a wide range of non-random label noises. Empirical studies using three real-world datasets with inherent annotation errors demonstrate that the proposed generalised label noise model improves, in terms of classification accuracy, over existing label noise modelling approaches. 2018-09-04T10:12:21Z 2018-09-04T10:12:21Z 2015-01-01 Conference Proceeding 2-s2.0-84961807046 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84961807046&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54356 |
| institution |
Chiang Mai University |
| building |
Chiang Mai University Library |
| country |
Thailand |
| collection |
CMU Intellectual Repository |
| topic |
Computer Science |
| spellingShingle |
Computer Science Jakramate Bootkrajang A generalised label noise model for classification |
| description |
Learning from labelled data is becoming more and more challenging due to inherent imperfection of training labels. In this paper, we propose a new, generalised label noise model which is able to withstand the negative effect of both random noise and a wide range of non-random label noises. Empirical studies using three real-world datasets with inherent annotation errors demonstrate that the proposed generalised label noise model improves, in terms of classification accuracy, over existing label noise modelling approaches. |
| format |
Conference Proceeding |
| author |
Jakramate Bootkrajang |
| author_facet |
Jakramate Bootkrajang |
| author_sort |
Jakramate Bootkrajang |
| title |
A generalised label noise model for classification |
| title_short |
A generalised label noise model for classification |
| title_full |
A generalised label noise model for classification |
| title_fullStr |
A generalised label noise model for classification |
| title_full_unstemmed |
A generalised label noise model for classification |
| title_sort |
generalised label noise model for classification |
| publishDate |
2018 |
| url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84961807046&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54356 |
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