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1
Analysis of classifiers’ robustness to adversarial perturbations
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Analysis of classifiers’ robustness to adversarial perturbations

Machine 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/s10994-017-5663-3

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2
Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review
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Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review

Remote sensing (Basel, Switzerland), 2020-04, Vol.12 (7), p.1135 [Peer Reviewed Journal]

ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12071135

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3
Quantum ensembles of quantum classifiers
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Quantum ensembles of quantum classifiers

Scientific 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: 29426855

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4
Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection
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Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection

Cell 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.2020.05.012

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5
A performance comparison of eight commercially available automatic classifiers for facial affect recognition
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A performance comparison of eight commercially available automatic classifiers for facial affect recognition

PloS 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: 32330178

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6
A review of epileptic seizure detection using machine learning classifiers
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Article
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A review of epileptic seizure detection using machine learning classifiers

Brain 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: 32451639

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7
Domain Adaptation for Statistical Classifiers
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Domain Adaptation for Statistical Classifiers

The 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.1872

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8
Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers
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Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers

NeuroImage (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: 24389422

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9
Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer
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Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer

Frontiers 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: 26697407

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10
Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery
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Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery

Sensors (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: 29271909

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11
The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets
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The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets

PloS 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: 25738806

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12
Machine learning classifiers and fMRI: A tutorial overview
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Article
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Machine learning classifiers and fMRI: A tutorial overview

NeuroImage (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: 19070668

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13
MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers
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Article
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MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers

Sensors (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: 33810176

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14
Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers
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Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers

Medical 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: 29763967

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15
Classifiers Combination Techniques: A Comprehensive Review
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Article
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Classifiers Combination Techniques: A Comprehensive Review

IEEE 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: IAECCG

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16
Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology
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Article
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Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology

Frontiers 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: 27064691

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17
Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study
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Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study

PloS 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: 26672989

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18
Decision tree classifiers for automated medical diagnosis
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Decision tree classifiers for automated medical diagnosis

Neural computing & applications, 2013-12, Vol.23 (7-8), p.2387-2403 [Peer Reviewed Journal]

Springer-Verlag London 2012 ;2014 INIST-CNRS ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-012-1196-7

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19
Features and classifiers for emotion recognition from speech: a survey from 2000 to 2011
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Features and classifiers for emotion recognition from speech: a survey from 2000 to 2011

The Artificial intelligence review, 2015-02, Vol.43 (2), p.155-177 [Peer Reviewed Journal]

Springer Science+Business Media Dordrecht 2012 ;COPYRIGHT 2015 Springer ;Springer Science+Business Media Dordrecht 2015 ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-012-9368-5

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20
A review of learning vector quantization classifiers
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A review of learning vector quantization classifiers

Neural computing & applications, 2014-09, Vol.25 (3-4), p.511-524 [Peer Reviewed Journal]

Springer-Verlag London 2013 ;2015 INIST-CNRS ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-013-1535-3

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