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21
Hyperspectral Imaging for Presymptomatic Detection of Tobacco Disease with Successive Projections Algorithm and Machine-learning Classifiers
Hyperspectral Imaging for Presymptomatic Detection of Tobacco Disease with Successive Projections Algorithm and Machine-learning Classifiers
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Hyperspectral Imaging for Presymptomatic Detection of Tobacco Disease with Successive Projections Algorithm and Machine-learning Classifiers

Scientific reports, 2017-06, Vol.7 (1), p.4125-12, Article 4125 [Peer Reviewed Journal]

Copyright Nature Publishing Group Jun 2017 ;The Author(s) 2017 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-017-04501-2 ;PMID: 28646177

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22
Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm
Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm
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Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm

PloS one, 2015-08, Vol.10 (8), p.e0134254-e0134254 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;2015 McDonnell 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 McDonnell et al 2015 McDonnell et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0134254 ;PMID: 26262687

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23
Machine unlearning: linear filtration for logit-based classifiers
Machine unlearning: linear filtration for logit-based classifiers
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Machine unlearning: linear filtration for logit-based classifiers

Machine learning, 2022-09, Vol.111 (9), p.3203-3226 [Peer Reviewed Journal]

The Author(s) 2022 ;The Author(s) 2022. 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: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-022-06178-9

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24
Classifier-based constraint acquisition
Classifier-based constraint acquisition
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Classifier-based constraint acquisition

Annals of mathematics and artificial intelligence, 2021-07, Vol.89 (7), p.655-674 [Peer Reviewed Journal]

The Author(s) 2021 ;ISSN: 1012-2443 ;EISSN: 1573-7470 ;DOI: 10.1007/s10472-021-09736-4

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25
Authorship attribution using author profiling classifiers
Authorship attribution using author profiling classifiers
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Authorship attribution using author profiling classifiers

Natural language engineering, 2023-01, Vol.29 (1), p.110-137 [Peer Reviewed Journal]

The Author(s), 2022. Published by Cambridge University Press ;ISSN: 1351-3249 ;EISSN: 1469-8110 ;DOI: 10.1017/S1351324921000383

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26
COVID-19 Detection from Cough Recordings Using Bag-of-Words Classifiers
COVID-19 Detection from Cough Recordings Using Bag-of-Words Classifiers
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COVID-19 Detection from Cough Recordings Using Bag-of-Words Classifiers

Sensors (Basel, Switzerland), 2023-05, Vol.23 (11), p.4996 [Peer Reviewed Journal]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 by the authors. 2023 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s23114996 ;PMID: 37299721

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27
Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification
Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification
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Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification

Remote sensing (Basel, Switzerland), 2019-07, Vol.11 (14), p.1713 [Peer Reviewed Journal]

2019. 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. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11141713

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28
A survey of deep network techniques all classifiers can adopt
A survey of deep network techniques all classifiers can adopt
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A survey of deep network techniques all classifiers can adopt

Data mining and knowledge discovery, 2021-01, Vol.35 (1), p.46-87 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020 ;The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00722-8 ;PMID: 34584490

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29
Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images
Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images
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Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images

Remote sensing (Basel, Switzerland), 2022-02, Vol.14 (3), p.574 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs14030574

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30
Classification of acute lymphoblastic leukaemia using hybrid hierarchical classifiers
Classification of acute lymphoblastic leukaemia using hybrid hierarchical classifiers
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Classification of acute lymphoblastic leukaemia using hybrid hierarchical classifiers

Multimedia tools and applications, 2017-09, Vol.76 (18), p.19057-19085 [Peer Reviewed Journal]

Springer Science+Business Media New York 2017 ;Multimedia Tools and Applications is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-017-4478-3

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31
SAR Oil Spill Detection System through Random Forest Classifiers
SAR Oil Spill Detection System through Random Forest Classifiers
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SAR Oil Spill Detection System through Random Forest Classifiers

Remote sensing (Basel, Switzerland), 2021-06, Vol.13 (11), p.2044 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs13112044

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32
Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability
Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability
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Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability

Sensors (Basel, Switzerland), 2022-04, Vol.22 (9), p.3314 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22093314 ;PMID: 35591006

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33
Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)
Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)
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Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)

Sensors (Basel, Switzerland), 2022-08, Vol.22 (17), p.6338 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22176338 ;PMID: 36080795

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34
Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers
Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers
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Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers

Sensors (Basel, Switzerland), 2022-09, Vol.22 (19), p.7227 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22197227 ;PMID: 36236325

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35
Cancer diagnosis through a tandem of classifiers for digitized histopathological slides
Cancer diagnosis through a tandem of classifiers for digitized histopathological slides
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Cancer diagnosis through a tandem of classifiers for digitized histopathological slides

PloS one, 2019-01, Vol.14 (1), p.e0209274-e0209274 [Peer Reviewed Journal]

COPYRIGHT 2019 Public Library of Science ;COPYRIGHT 2019 Public Library of Science ;2019 Lichtblau, Stoean. 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. ;2019 Lichtblau, Stoean 2019 Lichtblau, Stoean ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0209274 ;PMID: 30650087

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36
Hierarchical classification of protein folds using a novel ensemble classifier
Hierarchical classification of protein folds using a novel ensemble classifier
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Hierarchical classification of protein folds using a novel ensemble classifier

PloS one, 2013-02, Vol.8 (2), p.e56499-e56499 [Peer Reviewed Journal]

COPYRIGHT 2013 Public Library of Science ;COPYRIGHT 2013 Public Library of Science ;2013 Lin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://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. ;2013 Lin et al 2013 Lin et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0056499 ;PMID: 23437146

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37
Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
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Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression

Journal of clinical epidemiology, 2010-08, Vol.63 (8), p.826-833 [Peer Reviewed Journal]

Elsevier Inc. ;2010 Elsevier Inc. ;2015 INIST-CNRS ;Copyright (c) 2010 Elsevier Inc. All rights reserved. ;ISSN: 0895-4356 ;EISSN: 1878-5921 ;DOI: 10.1016/j.jclinepi.2009.11.020 ;PMID: 20630332

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38
Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images
Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images
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Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images

European journal of remote sensing, 2017-01, Vol.50 (1), p.144-154 [Peer Reviewed Journal]

2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2017 ;2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License 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: 2279-7254 ;EISSN: 2279-7254 ;DOI: 10.1080/22797254.2017.1299557

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39
Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method
Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method
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Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method

Sensors (Basel, Switzerland), 2021-04, Vol.21 (9), p.3006 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21093006 ;PMID: 33922957

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40
Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis
Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis
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Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis

Remote sensing (Basel, Switzerland), 2023-07, Vol.15 (14), p.3511 [Peer Reviewed Journal]

2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs15143511

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