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1 |
Material Type: Article
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Ensemble-based classifiersThe Artificial intelligence review, 2010-02, Vol.33 (1-2), p.1-39 [Peer Reviewed Journal]Springer Science+Business Media B.V. 2009 ;Springer Science+Business Media B.V. 2010 ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-009-9124-7Full text available |
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2 |
Material Type: Article
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Analysis of classifiers’ robustness to adversarial perturbationsMachine learning, 2018-03, Vol.107 (3), p.481-508 [Peer Reviewed Journal]The Author(s) 2017 ;Machine Learning is a copyright of Springer, (2017). All Rights Reserved. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-017-5663-3Full text available |
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3 |
Material Type: Article
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Clinicopathological and molecular characterisation of 'multiple-classifier' endometrial carcinomasThe Journal of pathology, 2020-03, Vol.250 (3), p.312 [Peer Reviewed Journal]ISSN: 1096-9896 ;EISSN: 1096-9896 ;DOI: 10.1002/path.5373Digital Resources/Online E-Resources |
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4 |
Material Type: Article
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Prediction of heart disease and classifiers’ sensitivity analysisBMC bioinformatics, 2020-07, Vol.21 (1), p.1-278, Article 278 [Peer Reviewed Journal]COPYRIGHT 2020 BioMed Central Ltd. ;2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2020 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-020-03626-y ;PMID: 32615980Full text available |
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Material Type: Article
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A systematic comparison of supervised classifiersPloS one, 2014-04, Vol.9 (4), p.e94137-e94137 [Peer Reviewed Journal]COPYRIGHT 2014 Public Library of Science ;COPYRIGHT 2014 Public Library of Science ;2014 Amancio et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2014 Amancio et al 2014 Amancio et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0094137 ;PMID: 24763312Full text available |
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Material Type: Article
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A performance comparison of eight commercially available automatic classifiers for facial affect recognitionPloS one, 2020-04, Vol.15 (4), p.e0231968-e0231968 [Peer Reviewed Journal]COPYRIGHT 2020 Public Library of Science ;COPYRIGHT 2020 Public Library of Science ;2020 Dupré et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Dupré et al 2020 Dupré et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0231968 ;PMID: 32330178Full text available |
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7 |
Material Type: Article
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Comprehensive benchmarking and ensemble approaches for metagenomic classifiersGenome Biology, 2017-09, Vol.18 (1), p.182-19, Article 182 [Peer Reviewed Journal]2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s). 2017 ;ISSN: 1474-760X ;ISSN: 1474-7596 ;EISSN: 1474-760X ;DOI: 10.1186/s13059-017-1299-7 ;PMID: 28934964Full text available |
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8 |
Material Type: Article
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Tag N’ Train: a technique to train improved classifiers on unlabeled dataThe journal of high energy physics, 2021-01, Vol.2021 (1), p.1-21, Article 153 [Peer Reviewed Journal]The Author(s) 2021 ;The Author(s) 2021. This work is published under CC-BY 4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1029-8479 ;EISSN: 1029-8479 ;DOI: 10.1007/JHEP01(2021)153Full text available |
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9 |
Material Type: Article
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One-class classifiersJournal of chemometrics, 2011-05, Vol.25 (5), p.225-246 [Peer Reviewed Journal]Copyright © 2011 John Wiley & Sons, Ltd. ;2015 INIST-CNRS ;ISSN: 0886-9383 ;ISSN: 1099-128X ;EISSN: 1099-128X ;DOI: 10.1002/cem.1397 ;CODEN: JOCHEUFull text available |
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10 |
Material Type: Article
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Nearest neighbors distance ratio open-set classifierMachine learning, 2017-03, Vol.106 (3), p.359-386 [Peer Reviewed Journal]The Author(s) 2016 ;Machine Learning is a copyright of Springer, 2017. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-016-5610-8Full text available |
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11 |
Material Type: Article
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Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiersNeuroImage (Orlando, Fla.), 2014-04, Vol.90, p.449-468 [Peer Reviewed Journal]2014 ;2015 INIST-CNRS ;Copyright © 2014. Published by Elsevier Inc. ;Copyright Elsevier Limited Apr 15, 2014 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2013.11.046 ;PMID: 24389422Full text available |
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12 |
Material Type: Article
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Optimal classifier for imbalanced data using Matthews Correlation Coefficient metricPloS one, 2017-06, Vol.12 (6), p.e0177678-e0177678 [Peer Reviewed Journal]COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Boughorbel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 Boughorbel et al 2017 Boughorbel et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0177678 ;PMID: 28574989Full text available |
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13 |
Material Type: Article
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Explaining classifiers by constructing familiar conceptsMachine learning, 2023-11, Vol.112 (11), p.4167-4200 [Peer Reviewed Journal]The Author(s) 2022 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-022-06157-0Digital Resources/Online E-Resources |
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14 |
Material Type: Article
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Classifier chains for multi-label classificationMachine learning, 2011-12, Vol.85 (3), p.333-359 [Peer Reviewed Journal]The Author(s) 2011 ;2015 INIST-CNRS ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-011-5256-5Full text available |
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15 |
Material Type: Article
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Differentiation of supratentorial single brain metastasis and glioblastoma by using peri-enhancing oedema region–derived radiomic features and multiple classifiersEuropean radiology, 2020-05, Vol.30 (5), p.3015-3022 [Peer Reviewed Journal]European Society of Radiology 2019 ;European Society of Radiology 2019. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06460-w ;PMID: 32006166Full text available |
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16 |
Material Type: Article
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Class-imbalanced classifiers for high-dimensional dataBriefings in bioinformatics, 2013-01, Vol.14 (1), p.13-26 [Peer Reviewed Journal]ISSN: 1467-5463 ;EISSN: 1477-4054 ;DOI: 10.1093/bib/bbs006 ;PMID: 22408190Full text available |
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17 |
Material Type: Article
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The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasetsPloS one, 2015-03, Vol.10 (3), p.e0118432-e0118432 [Peer Reviewed Journal]COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Saito, Rehmsmeier. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2015 Saito, Rehmsmeier 2015 Saito, Rehmsmeier ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0118432 ;PMID: 25738806Full text available |
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18 |
Material Type: Article
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Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 ImagerySensors (Basel, Switzerland), 2017-12, Vol.18 (1), p.18 [Peer Reviewed Journal]2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 by the authors. 2017 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s18010018 ;PMID: 29271909Full text available |
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19 |
Material Type: Article
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Machine learning classifiers and fMRI: A tutorial overviewNeuroImage (Orlando, Fla.), 2009-03, Vol.45 (1), p.S199-S209 [Peer Reviewed Journal]2008 Elsevier Inc. ;Copyright Elsevier Limited Mar 1, 2009 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2008.11.007 ;PMID: 19070668Full text available |
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20 |
Material Type: Article
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A geometric framework for multiclass ensemble classifiersMachine learning, 2023-12, Vol.112 (12), p.4929-4958 [Peer Reviewed Journal]The Author(s) 2023 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-023-06406-wDigital Resources/Online E-Resources |