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1
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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2
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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3
Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers
Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers
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Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers

NeuroImage (Orlando, Fla.), 2014-04, Vol.90, p.449-468 [Peer Reviewed Journal]

2014 ;2015 INIST-CNRS ;Copyright © 2014. Published by Elsevier Inc. ;Copyright Elsevier Limited Apr 15, 2014 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2013.11.046 ;PMID: 24389422

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4
Ensemble-based classifiers
Ensemble-based classifiers
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Ensemble-based classifiers

The Artificial intelligence review, 2010-02, Vol.33 (1-2), p.1-39 [Peer Reviewed Journal]

Springer Science+Business Media B.V. 2009 ;Springer Science+Business Media B.V. 2010 ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-009-9124-7

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5
Tree-based classifier ensembles for early detection method of diabetes: an exploratory study
Tree-based classifier ensembles for early detection method of diabetes: an exploratory study
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Tree-based classifier ensembles for early detection method of diabetes: an exploratory study

The Artificial intelligence review, 2019-03, Vol.51 (3), p.355-370 [Peer Reviewed Journal]

Springer Science+Business Media Dordrecht 2017 ;COPYRIGHT 2019 Springer ;Artificial Intelligence Review is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-017-9565-3

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6
Stochastic optimization for bayesian network classifiers
Stochastic optimization for bayesian network classifiers
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Stochastic optimization for bayesian network classifiers

Applied intelligence (Dordrecht, Netherlands), 2022-10, Vol.52 (13), p.15496-15516 [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: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-022-03356-z

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7
SVM ensemble training for imbalanced data classification using multi-objective optimization techniques
SVM ensemble training for imbalanced data classification using multi-objective optimization techniques
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SVM ensemble training for imbalanced data classification using multi-objective optimization techniques

Applied intelligence (Dordrecht, Netherlands), 2023-06, Vol.53 (12), p.15424-15441 [Peer Reviewed Journal]

The Author(s) 2022 ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-022-04291-9

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8
A semi-hard voting combiner scheme to ensemble multi-class probabilistic classifiers
A semi-hard voting combiner scheme to ensemble multi-class probabilistic classifiers
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A semi-hard voting combiner scheme to ensemble multi-class probabilistic classifiers

Applied intelligence (Dordrecht, Netherlands), 2022-03, Vol.52 (4), p.3653-3677 [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/s10489-021-02447-7

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9
Detecting Ordinal Subcascades
Detecting Ordinal Subcascades
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Detecting Ordinal Subcascades

Neural processing letters, 2020-12, Vol.52 (3), p.2583-2605 [Peer Reviewed Journal]

The Author(s) 2020 ;ISSN: 1370-4621 ;EISSN: 1573-773X ;DOI: 10.1007/s11063-020-10362-0

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10
Semi-supervised learning for k-dependence Bayesian classifiers
Semi-supervised learning for k-dependence Bayesian classifiers
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Semi-supervised learning for k-dependence Bayesian classifiers

Applied intelligence (Dordrecht, Netherlands), 2022-03, Vol.52 (4), p.3604-3622 [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/s10489-021-02531-y

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11
Large margin classifiers to generate synthetic data for imbalanced datasets
Large margin classifiers to generate synthetic data for imbalanced datasets
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Large margin classifiers to generate synthetic data for imbalanced datasets

Applied intelligence (Dordrecht, Netherlands), 2020-11, Vol.50 (11), p.3678-3694 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2020 ;Springer Science+Business Media, LLC, part of Springer Nature 2020. ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-020-01719-y

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12
Parallelized extreme learning machine for online data classification
Parallelized extreme learning machine for online data classification
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Parallelized extreme learning machine for online data classification

Applied intelligence (Dordrecht, Netherlands), 2022-09, Vol.52 (12), p.14164-14177 [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: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-022-03308-7

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13
A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning
A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning
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A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning

Applied intelligence (Dordrecht, Netherlands), 2021-02, Vol.51 (2), p.889-905 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2020 ;Springer Science+Business Media, LLC, part of Springer Nature 2020. ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-020-01839-5

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14
A tree-based stacking ensemble technique with feature selection for network intrusion detection
A tree-based stacking ensemble technique with feature selection for network intrusion detection
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A tree-based stacking ensemble technique with feature selection for network intrusion detection

Applied intelligence (Dordrecht, Netherlands), 2022-07, Vol.52 (9), p.9768-9781 [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: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-021-02968-1

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15
Concept learning using one-class classifiers for implicit drift detection in evolving data streams
Concept learning using one-class classifiers for implicit drift detection in evolving data streams
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Concept learning using one-class classifiers for implicit drift detection in evolving data streams

The Artificial intelligence review, 2021-06, Vol.54 (5), p.3725-3747 [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/s10462-020-09939-x

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16
A LightGBM-Based EEG Analysis Method for Driver Mental States Classification
A LightGBM-Based EEG Analysis Method for Driver Mental States Classification
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A LightGBM-Based EEG Analysis Method for Driver Mental States Classification

Computational intelligence and neuroscience, 2019-09, Vol.2019, p.1-11 [Peer Reviewed Journal]

Copyright © 2019 Hong Zeng et al. ;Copyright © 2019 Hong Zeng et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0 ;Copyright © 2019 Hong Zeng et al. 2019 ;ISSN: 1687-5265 ;EISSN: 1687-5273 ;DOI: 10.1155/2019/3761203 ;PMID: 31611912

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17
Handling Class-Imbalance with KNN (Neighbourhood) Under-Sampling for Software Defect Prediction
Handling Class-Imbalance with KNN (Neighbourhood) Under-Sampling for Software Defect Prediction
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Handling Class-Imbalance with KNN (Neighbourhood) Under-Sampling for Software Defect Prediction

The Artificial intelligence review, 2022-03, Vol.55 (3), p.2023-2064 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature B.V. 2021 ;COPYRIGHT 2022 Springer ;The Author(s), under exclusive licence to Springer Nature B.V. 2021. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-021-10044-w

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18
Unsupervised concept drift detection for multi-label data streams
Unsupervised concept drift detection for multi-label data streams
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Unsupervised concept drift detection for multi-label data streams

The Artificial intelligence review, 2023-03, Vol.56 (3), p.2401-2434 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature B.V. 2022 ;COPYRIGHT 2023 Springer ;The Author(s), under exclusive licence to Springer Nature B.V. 2022. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-022-10232-2

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19
Chaotic antlion algorithm for parameter optimization of support vector machine
Chaotic antlion algorithm for parameter optimization of support vector machine
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Chaotic antlion algorithm for parameter optimization of support vector machine

Applied intelligence (Dordrecht, Netherlands), 2018-03, Vol.48 (3), p.670-686 [Peer Reviewed Journal]

Springer Science+Business Media New York 2017 ;Applied Intelligence is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-017-0994-0

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20
DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique
DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique
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DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique

Applied intelligence (Dordrecht, Netherlands), 2012-04, Vol.36 (3), p.664-684 [Peer Reviewed Journal]

Springer Science+Business Media, LLC 2011 ;Springer Science+Business Media, LLC 2012 ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-011-0287-y

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