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1
An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach
An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach
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An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach

IEEE access, 2021, Vol.9, p.67488-67500 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2021.3075140 ;CODEN: IAECCG

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2
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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3
Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery
Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery
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Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery

Remote sensing (Basel, Switzerland), 2015-01, Vol.7 (1), p.153-168 [Peer Reviewed Journal]

Copyright MDPI AG 2015 ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs70100153

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4
Impact of SMOTE on Imbalanced Text Features for Toxic Comments Classification Using RVVC Model
Impact of SMOTE on Imbalanced Text Features for Toxic Comments Classification Using RVVC Model
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Impact of SMOTE on Imbalanced Text Features for Toxic Comments Classification Using RVVC Model

IEEE access, 2021, Vol.9, p.78621-78634 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2021.3083638 ;CODEN: IAECCG

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5
Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM
Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM
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Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM

Applied intelligence (Dordrecht, Netherlands), 2021-10, Vol.51 (10), p.7094-7108 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 ;The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021. ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-021-02205-9

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6
Experimental Comparisons of Multi-class Classifiers
Experimental Comparisons of Multi-class Classifiers
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Experimental Comparisons of Multi-class Classifiers

Informatica (Ljubljana), 2015-03, Vol.39 (1), p.71-71 [Peer Reviewed Journal]

Copyright Slovenian Society Informatika / Slovensko drustvo Informatika Mar 2015 ;ISSN: 0350-5596 ;EISSN: 1854-3871

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7
ECG Signal Preprocessing and SVM Classifier-Based Abnormality Detection in Remote Healthcare Applications
ECG Signal Preprocessing and SVM Classifier-Based Abnormality Detection in Remote Healthcare Applications
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ECG Signal Preprocessing and SVM Classifier-Based Abnormality Detection in Remote Healthcare Applications

IEEE access, 2018-01, Vol.6, p.9767-9773 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2018.2794346 ;CODEN: IAECCG

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8
Supervised learning with quantum-enhanced feature spaces
Supervised learning with quantum-enhanced feature spaces
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Supervised learning with quantum-enhanced feature spaces

Nature (London), 2019-03, Vol.567 (7747), p.209-212 [Peer Reviewed Journal]

COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Mar 14, 2019 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-019-0980-2 ;PMID: 30867609

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9
False-Alarm-Controllable Radar Detection for Marine Target Based on Multi Features Fusion via CNNs
False-Alarm-Controllable Radar Detection for Marine Target Based on Multi Features Fusion via CNNs
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False-Alarm-Controllable Radar Detection for Marine Target Based on Multi Features Fusion via CNNs

IEEE sensors journal, 2021-04, Vol.21 (7), p.9099-9111 [Peer Reviewed Journal]

ISSN: 1530-437X ;EISSN: 1558-1748 ;DOI: 10.1109/JSEN.2021.3054744 ;CODEN: ISJEAZ

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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
A comprehensive evaluation of ensemble learning for stock-market prediction
A comprehensive evaluation of ensemble learning for stock-market prediction
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A comprehensive evaluation of ensemble learning for stock-market prediction

Journal of big data, 2020-03, Vol.7 (1), p.1-40, Article 20 [Peer Reviewed Journal]

The Author(s) 2020 ;Journal of Big Data is a copyright of Springer, (2020). All Rights Reserved. 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: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-020-00299-5

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12
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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13
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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14
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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15
Comparison between Fisher's Ratio and Information Gain with SVM classifier for 3 levels of enthusiasm classification through face recognition
Comparison between Fisher's Ratio and Information Gain with SVM classifier for 3 levels of enthusiasm classification through face recognition
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Comparison between Fisher's Ratio and Information Gain with SVM classifier for 3 levels of enthusiasm classification through face recognition

Journal of physics. Conference series, 2021-02, Vol.1752 (1), p.12042 [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: 10.1088/1742-6596/1752/1/012042

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16
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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17
Problem formulations and solvers in linear SVM: a review
Problem formulations and solvers in linear SVM: a review
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Problem formulations and solvers in linear SVM: a review

The Artificial intelligence review, 2019-08, Vol.52 (2), p.803-855 [Peer Reviewed Journal]

Springer Science+Business Media B.V., part of Springer Nature 2018 ;COPYRIGHT 2019 Springer ;Artificial Intelligence Review is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-018-9614-6

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18
Automatic Sleep-Arousal Detection with Single-Lead EEG Using Stacking Ensemble Learning
Automatic Sleep-Arousal Detection with Single-Lead EEG Using Stacking Ensemble Learning
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Automatic Sleep-Arousal Detection with Single-Lead EEG Using Stacking Ensemble Learning

Sensors (Basel, Switzerland), 2021-09, Vol.21 (18), p.6049 [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/s21186049 ;PMID: 34577255

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19
Diabetic retinopathy classification based on multipath CNN and machine learning classifiers
Diabetic retinopathy classification based on multipath CNN and machine learning classifiers
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Diabetic retinopathy classification based on multipath CNN and machine learning classifiers

Australasian physical & engineering sciences in medicine, 2021-09, Vol.44 (3), p.639-653 [Peer Reviewed Journal]

Australasian College of Physical Scientists and Engineers in Medicine 2021. ;ISSN: 0158-9938 ;EISSN: 1879-5447 ;DOI: 10.1007/s13246-021-01012-3

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20
An Ensemble Approach for the Prediction of Diabetes Mellitus Using a Soft Voting Classifier with an Explainable AI
An Ensemble Approach for the Prediction of Diabetes Mellitus Using a Soft Voting Classifier with an Explainable AI
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An Ensemble Approach for the Prediction of Diabetes Mellitus Using a Soft Voting Classifier with an Explainable AI

Sensors (Basel, Switzerland), 2022-09, Vol.22 (19), p.7268 [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/s22197268 ;PMID: 36236367

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