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1
Classifiers Combination Techniques: A Comprehensive Review
Classifiers Combination Techniques: A Comprehensive Review
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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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2
An effective combining classifier approach using tree algorithms for network intrusion detection
An effective combining classifier approach using tree algorithms for network intrusion detection
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An effective combining classifier approach using tree algorithms for network intrusion detection

Neural computing & applications, 2017-12, Vol.28 (Suppl 1), p.1051-1058 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2016 ;Copyright Springer Science & Business Media 2017 ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-016-2418-1

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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
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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5
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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6
EMCNet: Automated COVID-19 diagnosis from X-ray images using convolutional neural network and ensemble of machine learning classifiers
EMCNet: Automated COVID-19 diagnosis from X-ray images using convolutional neural network and ensemble of machine learning classifiers
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EMCNet: Automated COVID-19 diagnosis from X-ray images using convolutional neural network and ensemble of machine learning classifiers

Informatics in medicine unlocked, 2021-01, Vol.22, p.100505-100505, Article 100505 [Peer Reviewed Journal]

2020 The Author(s) ;2020 The Author(s). ;2020 The Author(s) 2020 ;ISSN: 2352-9148 ;EISSN: 2352-9148 ;DOI: 10.1016/j.imu.2020.100505 ;PMID: 33363252

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7
Swarm Learning for decentralized and confidential clinical machine learning
Swarm Learning for decentralized and confidential clinical machine learning
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Swarm Learning for decentralized and confidential clinical machine learning

Nature (London), 2021-06, Vol.594 (7862), p.265-270 [Peer Reviewed Journal]

COPYRIGHT 2021 Nature Publishing Group ;Copyright Nature Publishing Group Jun 10, 2021 ;The Author(s) 2021 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-021-03583-3 ;PMID: 34040261

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8
A review of epileptic seizure detection using machine learning classifiers
A review of epileptic seizure detection using machine learning classifiers
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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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9
ilastik: interactive machine learning for (bio)image analysis
ilastik: interactive machine learning for (bio)image analysis
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ilastik: interactive machine learning for (bio)image analysis

Nature methods, 2019-12, Vol.16 (12), p.1226-1232 [Peer Reviewed Journal]

COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Dec 2019 ;ISSN: 1548-7091 ;EISSN: 1548-7105 ;DOI: 10.1038/s41592-019-0582-9 ;PMID: 31570887

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10
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods
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Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods

Machine learning, 2021-03, Vol.110 (3), p.457-506 [Peer Reviewed Journal]

The Author(s) 2021 ;The Author(s) 2021. 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/s10994-021-05946-3

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11
An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition
An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition
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An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition

Sensors (Basel, Switzerland), 2017-09, Vol.17 (9), p.2020 [Peer Reviewed Journal]

Copyright MDPI AG 2017 ;2017 by the authors. 2017 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s17092020 ;PMID: 28869537

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12
Performance Evaluation of Error-Correcting Output Coding Based on Noisy and Noiseless Binary Classifiers
Performance Evaluation of Error-Correcting Output Coding Based on Noisy and Noiseless Binary Classifiers
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Performance Evaluation of Error-Correcting Output Coding Based on Noisy and Noiseless Binary Classifiers

International journal of neural systems, 2023-02, Vol.33 (2) [Peer Reviewed Journal]

2023, The Author(s) ;ISSN: 0129-0657 ;EISSN: 1793-6462 ;DOI: 10.1142/S0129065723500041

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13
ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels
ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels
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ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels

Data mining and knowledge discovery, 2020-09, Vol.34 (5), p.1454-1495 [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/s10618-020-00701-z

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14
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
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On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

PloS one, 2015-07, Vol.10 (7), p.e0130140-e0130140 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Bach 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 Bach et al 2015 Bach et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0130140 ;PMID: 26161953

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15
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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16
Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery
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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17
The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets
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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18
A Review of Emotion Recognition Using Physiological Signals
A Review of Emotion Recognition Using Physiological Signals
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A Review of Emotion Recognition Using Physiological Signals

Sensors (Basel, Switzerland), 2018-06, Vol.18 (7), p.2074 [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. ;2018 by the authors. 2018 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s18072074 ;PMID: 29958457

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19
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network
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Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network

Sensors (Basel, Switzerland), 2021-04, Vol.21 (9), p.3046 [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/s21093046 ;PMID: 33925371

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20
Object-Based Change Detection in Urban Areas from High Spatial Resolution Images Based on Multiple Features and Ensemble Learning
Object-Based Change Detection in Urban Areas from High Spatial Resolution Images Based on Multiple Features and Ensemble Learning
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Object-Based Change Detection in Urban Areas from High Spatial Resolution Images Based on Multiple Features and Ensemble Learning

Remote sensing (Basel, Switzerland), 2018-02, Vol.10 (2), p.276 [Peer Reviewed Journal]

Copyright MDPI AG 2018 ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs10020276

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