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| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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| 1 |
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 |
| 2 |
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Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A ReviewRemote sensing (Basel, Switzerland), 2020-04, Vol.12 (7), p.1135 [Peer Reviewed Journal]ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12071135Full text available |
| 3 |
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Quantum ensembles of quantum classifiersScientific reports, 2018-02, Vol.8 (1), p.2772-12, Article 2772 [Peer Reviewed Journal]Copyright Nature Publishing Group Feb 2018 ;The Author(s) 2018 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-018-20403-3 ;PMID: 29426855Full text available |
| 4 |
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Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infectionCell Systems, 2020-07, Vol.11 (1), p.11 [Peer Reviewed Journal]2020. Not withstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.elsevier.com/legal/elsevier-website-terms-and-conditions ;ISSN: 2405-4720 ;ISSN: 2405-4712 ;EISSN: 2405-4720 ;DOI: 10.1016/j.cels.2020.05.012Digital Resources/Online E-Resources |
| 5 |
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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 |
| 6 |
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A review of epileptic seizure detection using machine learning classifiersBrain informatics, 2020-05, Vol.7 (1), p.5-5, Article 5 [Peer Reviewed Journal]The Author(s) 2020 ;COPYRIGHT 2020 Springer ;The Author(s) 2020. This work is published 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. ;ISSN: 2198-4018 ;EISSN: 2198-4026 ;DOI: 10.1186/s40708-020-00105-1 ;PMID: 32451639Full text available |
| 7 |
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Domain Adaptation for Statistical ClassifiersThe Journal of artificial intelligence research, 2006-01, Vol.26, p.101-126 [Peer Reviewed Journal]2006. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.1872Full text available |
| 8 |
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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 |
| 9 |
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 |
| 10 |
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 |
| 11 |
Material Type: Article
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Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck CancerFrontiers in oncology, 2015-12, Vol.5, p.272-272 [Peer Reviewed Journal]COPYRIGHT 2015 Frontiers Research Foundation ;Copyright © 2015 Parmar, Grossmann, Rietveld, Rietbergen, Lambin and Aerts. 2015 Parmar, Grossmann, Rietveld, Rietbergen, Lambin and Aerts ;ISSN: 2234-943X ;EISSN: 2234-943X ;DOI: 10.3389/fonc.2015.00272 ;PMID: 26697407Full text available |
| 12 |
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 |
| 13 |
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 |
| 14 |
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 |
| 15 |
Material Type: Article
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MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning ClassifiersSensors (Basel, Switzerland), 2021-03, Vol.21 (6), p.2222 [Peer Reviewed Journal]2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21062222 ;PMID: 33810176Full text available |
| 16 |
Material Type: Article
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Exploratory Study to Identify Radiomics Classifiers for Lung Cancer HistologyFrontiers in oncology, 2016-03, Vol.6, p.71-71 [Peer Reviewed Journal]Copyright © 2016 Wu, Parmar, Grossmann, Quackenbush, Lambin, Bussink, Mak and Aerts. 2016 Wu, Parmar, Grossmann, Quackenbush, Lambin, Bussink, Mak and Aerts ;ISSN: 2234-943X ;EISSN: 2234-943X ;DOI: 10.3389/fonc.2016.00071 ;PMID: 27064691Full text available |
| 17 |
Material Type: Article
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Classifiers Combination Techniques: A Comprehensive ReviewIEEE access, 2018-01, Vol.6, p.19626-19639 [Peer Reviewed Journal]Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2018.2813079 ;CODEN: IAECCGFull text available |
| 18 |
Material Type: Article
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Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiersMedical physics (Lancaster), 2018-07, Vol.45 (7), p.3449-3459 [Peer Reviewed Journal]2018 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine. ;ISSN: 0094-2405 ;EISSN: 2473-4209 ;DOI: 10.1002/mp.12967 ;PMID: 29763967Full text available |
| 19 |
Material Type: Article
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Galaxy Merger Rates up to z ∼ 3 Using a Bayesian Deep Learning Model: A Major-merger Classifier Using IllustrisTNG Simulation DataThe Astrophysical journal, 2020-06, Vol.895 (2), p.115 [Peer Reviewed Journal]2020. The American Astronomical Society. All rights reserved. ;Copyright IOP Publishing Jun 01, 2020 ;ISSN: 0004-637X ;EISSN: 1538-4357 ;DOI: 10.3847/1538-4357/ab8f9bFull text available |
| 20 |
Material Type: Article
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Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison StudyPloS one, 2015-12, Vol.10 (12), p.e0145118-e0145118 [Peer Reviewed Journal]COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Maier 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. ;2015 Maier et al 2015 Maier et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0145118 ;PMID: 26672989Full text available |
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