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1
Dementia classification using MR imaging and clinical data with voting based machine learning models
Dementia classification using MR imaging and clinical data with voting based machine learning models
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Dementia classification using MR imaging and clinical data with voting based machine learning models

Multimedia tools and applications, 2022-07, Vol.81 (18), p.25971-25992 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 ;The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-022-12754-x

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2
EEG-Based Emotion Classification Using Stacking Ensemble Approach
EEG-Based Emotion Classification Using Stacking Ensemble Approach
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EEG-Based Emotion Classification Using Stacking Ensemble Approach

Sensors (Basel, Switzerland), 2022-11, Vol.22 (21), p.8550 [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/s22218550 ;PMID: 36366249

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3
Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier
Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier
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Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier

Computers in biology and medicine, 2020-08, Vol.123, p.103899, Article 103899 [Peer Reviewed Journal]

2020 Elsevier Ltd ;Copyright © 2020 Elsevier Ltd. All rights reserved. ;2020. Elsevier Ltd ;ISSN: 0010-4825 ;EISSN: 1879-0534 ;DOI: 10.1016/j.compbiomed.2020.103899 ;PMID: 32768046

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4
nDNA-Prot: identification of DNA-binding proteins based on unbalanced classification
nDNA-Prot: identification of DNA-binding proteins based on unbalanced classification
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nDNA-Prot: identification of DNA-binding proteins based on unbalanced classification

BMC bioinformatics, 2014-09, Vol.15 (1), p.298-298, Article 298 [Peer Reviewed Journal]

COPYRIGHT 2014 BioMed Central Ltd. ;2014 Song 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. ;Song et al.; licensee BioMed Central Ltd. 2014 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/1471-2105-15-298 ;PMID: 25196432

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5
Phishing Detection System through Hybrid Machine Learning Based on URL
Phishing Detection System through Hybrid Machine Learning Based on URL
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Phishing Detection System through Hybrid Machine Learning Based on URL

IEEE access, 2023-01, Vol.11, p.1-1 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2023.3252366 ;CODEN: IAECCG

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6
Interpretable time series classification using linear models and multi-resolution multi-domain symbolic representations
Interpretable time series classification using linear models and multi-resolution multi-domain symbolic representations
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Interpretable time series classification using linear models and multi-resolution multi-domain symbolic representations

Data mining and knowledge discovery, 2019-07, Vol.33 (4), p.1183-1222 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2019 ;Data Mining and Knowledge Discovery is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-019-00633-3

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7
Accuracy Improvement of Transformer Faults Diagnostic Based on DGA Data Using SVM-BA Classifier
Accuracy Improvement of Transformer Faults Diagnostic Based on DGA Data Using SVM-BA Classifier
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Accuracy Improvement of Transformer Faults Diagnostic Based on DGA Data Using SVM-BA Classifier

Energies (Basel), 2021-05, Vol.14 (10), p.2970 [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: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en14102970

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8
CICIDS-2017 Dataset Feature Analysis With Information Gain for Anomaly Detection
CICIDS-2017 Dataset Feature Analysis With Information Gain for Anomaly Detection
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CICIDS-2017 Dataset Feature Analysis With Information Gain for Anomaly Detection

IEEE access, 2020, Vol.8, p.132911-132921 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2020.3009843 ;CODEN: IAECCG

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9
Use of support vector machine and cellular automata methods to evaluate impact of irrigation project on LULC
Use of support vector machine and cellular automata methods to evaluate impact of irrigation project on LULC
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Use of support vector machine and cellular automata methods to evaluate impact of irrigation project on LULC

Environmental monitoring and assessment, 2023-01, Vol.195 (1), p.3-3, Article 3 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;ISSN: 0167-6369 ;EISSN: 1573-2959 ;DOI: 10.1007/s10661-022-10588-6

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10
Sensor Failure Tolerable Machine Learning-Based Food Quality Prediction Model
Sensor Failure Tolerable Machine Learning-Based Food Quality Prediction Model
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Sensor Failure Tolerable Machine Learning-Based Food Quality Prediction Model

Sensors (Basel, Switzerland), 2020-06, Vol.20 (11), p.3173 [Peer Reviewed Journal]

2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). 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/s20113173 ;PMID: 32503198

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11
Arabic text classification: the need for multi-labeling systems
Arabic text classification: the need for multi-labeling systems
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Arabic text classification: the need for multi-labeling systems

Neural computing & applications, 2022-01, Vol.34 (2), p.1135-1159 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021 ;The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-021-06390-z ;PMID: 34483495

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12
Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors
Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors
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Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors

Sensors (Basel, Switzerland), 2017-05, Vol.17 (6), p.1229 [Peer Reviewed Journal]

2017. 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/s17061229 ;PMID: 28555016

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13
Machine Learning Challenges for IoT Device Fingerprints Identification
Machine Learning Challenges for IoT Device Fingerprints Identification
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Machine Learning Challenges for IoT Device Fingerprints Identification

Journal of physics. Conference series, 2021-07, Vol.1963 (1), p.12046 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1963/1/012046

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14
Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation
Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation
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Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation

Remote sensing (Basel, Switzerland), 2021-11, Vol.13 (21), p.4405 [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/rs13214405

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15
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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16
A comparative analysis of gradient boosting algorithms
A comparative analysis of gradient boosting algorithms
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A comparative analysis of gradient boosting algorithms

The Artificial intelligence review, 2021-03, Vol.54 (3), p.1937-1967 [Peer Reviewed Journal]

Springer Nature B.V. 2020 ;COPYRIGHT 2021 Springer ;Springer Nature B.V. 2020. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-020-09896-5

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17
Classification of EEG Using Adaptive SVM Classifier with CSP and Online Recursive Independent Component Analysis
Classification of EEG Using Adaptive SVM Classifier with CSP and Online Recursive Independent Component Analysis
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Classification of EEG Using Adaptive SVM Classifier with CSP and Online Recursive Independent Component Analysis

Sensors (Basel, Switzerland), 2022-10, Vol.22 (19), p.7596 [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/s22197596 ;PMID: 36236694

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18
Improving Adversarial Robustness of Ensemble Classifiers by Diversified Feature Selection and Stochastic Aggregation
Improving Adversarial Robustness of Ensemble Classifiers by Diversified Feature Selection and Stochastic Aggregation
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Improving Adversarial Robustness of Ensemble Classifiers by Diversified Feature Selection and Stochastic Aggregation

Mathematics (Basel), 2024-03, Vol.12 (6), p.834 [Peer Reviewed Journal]

COPYRIGHT 2024 MDPI AG ;2024 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: 2227-7390 ;EISSN: 2227-7390 ;DOI: 10.3390/math12060834

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19
DeepLocate: Smartphone Based Indoor Localization with a Deep Neural Network Ensemble Classifier
DeepLocate: Smartphone Based Indoor Localization with a Deep Neural Network Ensemble Classifier
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DeepLocate: Smartphone Based Indoor Localization with a Deep Neural Network Ensemble Classifier

Sensors (Basel, Switzerland), 2019-12, Vol.20 (1), p.133 [Peer Reviewed Journal]

2019 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. ;2019 by the authors. 2019 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s20010133 ;PMID: 31878233

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20
Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion
Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion
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Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion

Plants (Basel), 2020-10, Vol.9 (10), p.1302 [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: 2223-7747 ;EISSN: 2223-7747 ;DOI: 10.3390/plants9101302 ;PMID: 33019765

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