Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/9415
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Slivka, Jelena | en |
dc.contributor.author | Zhang P. | en |
dc.contributor.author | Kovačević, Aleksandar | en |
dc.contributor.author | Konjović Z. | en |
dc.contributor.author | Budakov Obradović, Zorana | en |
dc.date.accessioned | 2019-09-30T09:15:45Z | - |
dc.date.available | 2019-09-30T09:15:45Z | - |
dc.date.issued | 2012-12-01 | en |
dc.identifier.isbn | 9780769549132 | en |
dc.identifier.uri | https://open.uns.ac.rs/handle/123456789/9415 | - |
dc.description.abstract | We propose a novel semi-supervised learning algorithm, called IMCC, designed for co-training classifiers on single-view datasets. Our method runs the co-training algorithm for a predefined number of times, each time using a different random split of features. Thus, a set of diverse co-training classifiers is created. Each of these classifiers then labels each of the examples for which we want to determine the class label. In this way, each example for classification is assigned multiple labels. We then treat this as a problem of learning from inconsistent and unreliable annotators in a multi-annotator problem setting and estimate the single hidden true label for each example. In experimental results obtained on 25 benchmark datasets of various properties IMCC outperformed five considered alternative methods for co-training on single-view datasets, and resulted in a statistical tie with a Naive Bayes classifier trained using a much larger set of labeled examples. © 2012 IEEE. | en |
dc.relation.ispartof | Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012 | en |
dc.title | Semi-supervised learning on single-view datasets by integration of multiple co-trained classifiers | en |
dc.type | Conference Paper | en |
dc.identifier.doi | 10.1109/ICMLA.2012.83 | en |
dc.identifier.scopus | 2-s2.0-84873607124 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/84873607124 | en |
dc.relation.lastpage | 463 | en |
dc.relation.firstpage | 458 | en |
dc.relation.volume | 1 | en |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Departman za računarstvo i automatiku | - |
crisitem.author.dept | Departman za računarstvo i automatiku | - |
crisitem.author.dept | Katedra za internu medicinu | - |
crisitem.author.parentorg | Fakultet tehničkih nauka | - |
crisitem.author.parentorg | Fakultet tehničkih nauka | - |
crisitem.author.parentorg | Medicinski fakultet | - |
Appears in Collections: | FTN Publikacije/Publications |
SCOPUSTM
Citations
2
checked on Nov 20, 2023
Page view(s)
33
Last Week
6
6
Last month
0
0
checked on May 3, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.