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21
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis

Applied intelligence (Dordrecht, Netherlands), 2019-05, Vol.49 (5), p.1688-1707 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2018 ;Applied Intelligence is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-018-1334-8

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22
An unsupervised one-class-classifier support vector machine to simultaneously monitor location and scale of multivariate quality characteristics
An unsupervised one-class-classifier support vector machine to simultaneously monitor location and scale of multivariate quality characteristics
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An unsupervised one-class-classifier support vector machine to simultaneously monitor location and scale of multivariate quality characteristics

The International journal of quality & reliability management, 2023-01, Vol.40 (2), p.419-454 [Peer Reviewed Journal]

Emerald Publishing Limited ;Emerald Publishing Limited. ;ISSN: 0265-671X ;EISSN: 1758-6682 ;DOI: 10.1108/IJQRM-09-2021-0316

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23
Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier
Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier
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Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier

Journal of medical systems, 2017-10, Vol.41 (10), p.160-160, Article 160 [Peer Reviewed Journal]

Springer Science+Business Media, LLC 2017 ;Journal of Medical Systems is a copyright of Springer, 2017. ;ISSN: 0148-5598 ;EISSN: 1573-689X ;DOI: 10.1007/s10916-017-0800-x ;PMID: 28866731

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24
Machine learning, medical diagnosis, and biomedical engineering research - commentary
Machine learning, medical diagnosis, and biomedical engineering research - commentary
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Machine learning, medical diagnosis, and biomedical engineering research - commentary

Biomedical engineering online, 2014-07, Vol.13 (1), p.94-94 [Peer Reviewed Journal]

COPYRIGHT 2014 BioMed Central Ltd. ;2014 Foster et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. ;Copyright © 2014 Foster et al.; licensee BioMed Central Ltd. 2014 Foster et al.; licensee BioMed Central Ltd. ;ISSN: 1475-925X ;EISSN: 1475-925X ;DOI: 10.1186/1475-925X-13-94 ;PMID: 24998888

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25
Ensemble of a subset of kNN classifiers
Ensemble of a subset of kNN classifiers
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Ensemble of a subset of kNN classifiers

Advances in data analysis and classification, 2018, Vol.12 (4), p.827-840 [Peer Reviewed Journal]

The Author(s) 2016 ;Advances in Data Analysis and Classification is a copyright of Springer, (2016). All Rights Reserved. © 2016. 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: 1862-5347 ;EISSN: 1862-5355 ;DOI: 10.1007/s11634-015-0227-5 ;PMID: 30931011

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26
Analysis and prediction of human acetylation using a cascade classifier based on support vector machine
Analysis and prediction of human acetylation using a cascade classifier based on support vector machine
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Analysis and prediction of human acetylation using a cascade classifier based on support vector machine

BMC bioinformatics, 2019-06, Vol.20 (1), p.346-346, Article 346 [Peer Reviewed Journal]

COPYRIGHT 2019 BioMed Central Ltd. ;2019. 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). 2019 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-019-2938-7 ;PMID: 31208321

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27
CarSite-II: an integrated classification algorithm for identifying carbonylated sites based on K-means similarity-based undersampling and synthetic minority oversampling techniques
CarSite-II: an integrated classification algorithm for identifying carbonylated sites based on K-means similarity-based undersampling and synthetic minority oversampling techniques
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CarSite-II: an integrated classification algorithm for identifying carbonylated sites based on K-means similarity-based undersampling and synthetic minority oversampling techniques

BMC bioinformatics, 2021-04, Vol.22 (1), p.216-216, Article 216 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. 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) 2021 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-021-04134-3 ;PMID: 33902446

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28
Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma
Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma
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Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma

European radiology, 2018-04, Vol.28 (4), p.1625-1633 [Peer Reviewed Journal]

European Society of Radiology 2017 ;European Radiology is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-017-5118-z ;PMID: 29134348

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29
High-impedance fault detection in medium-voltage distribution network using computational intelligence-based classifiers
High-impedance fault detection in medium-voltage distribution network using computational intelligence-based classifiers
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High-impedance fault detection in medium-voltage distribution network using computational intelligence-based classifiers

Neural computing & applications, 2019-12, Vol.31 (12), p.9127-9143 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2019 ;Neural Computing and Applications is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-019-04445-w

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30
Prediction of heart disease and classifiers’ sensitivity analysis
Prediction of heart disease and classifiers’ sensitivity analysis
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Prediction of heart disease and classifiers’ sensitivity analysis

BMC 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: 32615980

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31
A systematic comparison of supervised classifiers
A systematic comparison of supervised classifiers
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A systematic comparison of supervised classifiers

PloS 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: 24763312

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32
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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33
An Automated Machine-Learning Approach for Road Pothole Detection Using Smartphone Sensor Data
An Automated Machine-Learning Approach for Road Pothole Detection Using Smartphone Sensor Data
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An Automated Machine-Learning Approach for Road Pothole Detection Using Smartphone Sensor Data

Sensors (Basel, Switzerland), 2020-09, Vol.20 (19), p.5564 [Peer Reviewed Journal]

2020 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 (http://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. ;2020 by the authors. 2020 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s20195564 ;PMID: 32998427

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34
Software Defect Prediction Using an Intelligent Ensemble-Based Model
Software Defect Prediction Using an Intelligent Ensemble-Based Model
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Software Defect Prediction Using an Intelligent Ensemble-Based Model

IEEE access, 2024, Vol.12, p.20376-20395 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2024.3358201 ;CODEN: IAECCG

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35
An Integrated Index for the Identification of Diabetic Retinopathy Stages Using Texture Parameters
An Integrated Index for the Identification of Diabetic Retinopathy Stages Using Texture Parameters
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An Integrated Index for the Identification of Diabetic Retinopathy Stages Using Texture Parameters

Journal of medical systems, 2012-06, Vol.36 (3), p.2011-2020 [Peer Reviewed Journal]

Springer Science+Business Media, LLC 2011 ;Springer Science+Business Media, LLC 2012 ;ISSN: 0148-5598 ;EISSN: 1573-689X ;DOI: 10.1007/s10916-011-9663-8 ;PMID: 21340703

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36
Investigating Performance Trends of Simulated Real-time Solar Flare Predictions: The Impacts of Training Windows, Data Volumes, and the Solar Cycle
Investigating Performance Trends of Simulated Real-time Solar Flare Predictions: The Impacts of Training Windows, Data Volumes, and the Solar Cycle
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Investigating Performance Trends of Simulated Real-time Solar Flare Predictions: The Impacts of Training Windows, Data Volumes, and the Solar Cycle

The Astrophysical journal, 2024-04, Vol.964 (2), p.163 [Peer Reviewed Journal]

2024. The Author(s). Published by the American Astronomical Society. 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: 0004-637X ;EISSN: 1538-4357 ;DOI: 10.3847/1538-4357/ad276c

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37
A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections
A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections
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A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections

Nature communications, 2020-03, Vol.11 (1), p.1177-1177, Article 1177 [Peer Reviewed Journal]

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. ;The Author(s) 2020 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-020-14975-w ;PMID: 32132525

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38
Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery
Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery
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Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery

Remote sensing (Basel, Switzerland), 2014-02, Vol.6 (2), p.964-983 [Peer Reviewed Journal]

Copyright MDPI AG 2014 ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs6020964

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39
Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier
Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier
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Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier

World wide web (Bussum), 2017-03, Vol.20 (2), p.135-154 [Peer Reviewed Journal]

Springer Science+Business Media New York 2016 ;World Wide Web is a copyright of Springer, 2017. ;ISSN: 1386-145X ;EISSN: 1573-1413 ;DOI: 10.1007/s11280-015-0381-x

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40
A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers
A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers
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A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers

Molecules (Basel, Switzerland), 2020-09, Vol.25 (19), p.4353 [Peer Reviewed Journal]

2020 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 (http://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. ;2020 by the authors. 2020 ;ISSN: 1420-3049 ;EISSN: 1420-3049 ;DOI: 10.3390/molecules25194353 ;PMID: 32977371

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