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1
Nearest neighbors distance ratio open-set classifier
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Article
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Nearest neighbors distance ratio open-set classifier

Machine learning, 2017-03, Vol.106 (3), p.359-386 [Peer Reviewed Journal]

The Author(s) 2016 ;Machine Learning is a copyright of Springer, 2017. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-016-5610-8

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2
GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms
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GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

Di xue qian yuan., 2021-03, Vol.12 (2), p.857-876 [Peer Reviewed Journal]

2021 Elsevier B.V. ;Copyright Elsevier Science Ltd. Mar 2021 ;Copyright © Wanfang Data Co. Ltd. All Rights Reserved. ;ISSN: 1674-9871 ;EISSN: 2588-9192 ;DOI: 10.1016/j.gsf.2020.09.004

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3
Prediction of Skin Disease Using Ensemble Data Mining Techniques and Feature Selection Method—a Comparative Study
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Prediction of Skin Disease Using Ensemble Data Mining Techniques and Feature Selection Method—a Comparative Study

Applied biochemistry and biotechnology, 2020-02, Vol.190 (2), p.341-359 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2019 ;Applied Biochemistry and Biotechnology is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0273-2289 ;EISSN: 1559-0291 ;DOI: 10.1007/s12010-019-03093-z ;PMID: 31350666

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4
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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5
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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6
Machine learning classification can reduce false positives in structure-based virtual screening
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Machine learning classification can reduce false positives in structure-based virtual screening

Proceedings of the National Academy of Sciences - PNAS, 2020-08, Vol.117 (31), p.18477-18488 [Peer Reviewed Journal]

Copyright National Academy of Sciences Aug 4, 2020 ;Copyright © 2020 the Author(s). Published by PNAS. 2020 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2000585117 ;PMID: 32669436

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7
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
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The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances

Data mining and knowledge discovery, 2021-03, Vol.35 (2), p.401-449 [Peer Reviewed Journal]

The Author(s) 2020 ;The Author(s) 2020. ;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: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00727-3 ;PMID: 33679210

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8
A Random Forest classifier-based approach in the detection of abnormalities in the retina
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A Random Forest classifier-based approach in the detection of abnormalities in the retina

Medical & biological engineering & computing, 2019, Vol.57 (1), p.193-203 [Peer Reviewed Journal]

International Federation for Medical and Biological Engineering 2018 ;Medical & Biological Engineering & Computing is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0140-0118 ;EISSN: 1741-0444 ;DOI: 10.1007/s11517-018-1878-0 ;PMID: 30076537

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9
Diabetes Prediction Using Ensembling of Different Machine Learning Classifiers
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Diabetes Prediction Using Ensembling of Different Machine Learning Classifiers

IEEE access, 2020, Vol.8, p.76516-76531 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2020.2989857 ;CODEN: IAECCG

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10
Tweets Classification on the Base of Sentiments for US Airline Companies
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Tweets Classification on the Base of Sentiments for US Airline Companies

Entropy (Basel, Switzerland), 2019-11, Vol.21 (11), p.1078 [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: 1099-4300 ;EISSN: 1099-4300 ;DOI: 10.3390/e21111078

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11
A review of epileptic seizure detection using machine learning classifiers
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Article
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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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12
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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13
Machine learning reduced workload with minimal risk of missing studies: development and evaluation of a randomized controlled trial classifier for Cochrane Reviews
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Article
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Machine learning reduced workload with minimal risk of missing studies: development and evaluation of a randomized controlled trial classifier for Cochrane Reviews

Journal of clinical epidemiology, 2021-05, Vol.133, p.140-151 [Peer Reviewed Journal]

2020 The Authors ;Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved. ;2020. The Authors ;2020 The Authors 2020 ;ISSN: 0895-4356 ;EISSN: 1878-5921 ;DOI: 10.1016/j.jclinepi.2020.11.003 ;PMID: 33171275

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14
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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15
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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16
Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM
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Article
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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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17
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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18
Interpretable time series classification using linear models and multi-resolution multi-domain symbolic representations
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Article
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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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19
Experimental Comparisons of Multi-class Classifiers
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Article
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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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20
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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