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1
Nearest neighbors distance ratio open-set classifier
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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 ;ISSN: 1573-0565 ;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
Multiple classifier system for remote sensing image classification: a review
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Multiple classifier system for remote sensing image classification: a review

Sensors, 2012-04, Vol.12 (4), p.4764-4792 [Peer Reviewed Journal]

Copyright MDPI AG 2012 ;2012 by the authors; licensee MDPI, Basel, Switzerland. 2012 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s120404764 ;PMID: 22666057

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4
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 ;ISSN: 1091-6490 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2000585117 ;PMID: 32669436

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5
A hybrid hierarchical framework for classification of breast density using digitized film screen mammograms
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A hybrid hierarchical framework for classification of breast density using digitized film screen mammograms

Multimedia tools and applications, 2017-09, Vol.76 (18), p.18789-18813 [Peer Reviewed Journal]

Springer Science+Business Media New York 2017 ;Multimedia Tools and Applications is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-016-4340-z

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6
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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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 ;ISSN: 1878-5921 ;EISSN: 1878-5921 ;DOI: 10.1016/j.jclinepi.2020.11.003 ;PMID: 33171275

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7
Two-Stage Hybrid Data Classifiers Based on SVM and kNN Algorithms
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Two-Stage Hybrid Data Classifiers Based on SVM and kNN Algorithms

Symmetry (Basel), 2021-04, Vol.13 (4), p.615 [Peer Reviewed Journal]

2021 by the author. 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: 2073-8994 ;EISSN: 2073-8994 ;DOI: 10.3390/sym13040615

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8
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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9
Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric
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Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric

PloS one, 2017-06, Vol.12 (6), p.e0177678-e0177678 [Peer Reviewed Journal]

COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Boughorbel 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. ;2017 Boughorbel et al 2017 Boughorbel et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0177678 ;PMID: 28574989

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10
Discrimination of Mine Seismic Events and Blasts Using the Fisher Classifier, Naive Bayesian Classifier and Logistic Regression
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Discrimination of Mine Seismic Events and Blasts Using the Fisher Classifier, Naive Bayesian Classifier and Logistic Regression

Rock mechanics and rock engineering, 2016-01, Vol.49 (1), p.183-211 [Peer Reviewed Journal]

Springer-Verlag Wien 2015 ;Springer-Verlag Wien 2016 ;ISSN: 0723-2632 ;EISSN: 1434-453X ;DOI: 10.1007/s00603-015-0733-y

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11
Hybrid classifier based life cycle stages analysis for malaria-infected erythrocyte using thin blood smear images
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Hybrid classifier based life cycle stages analysis for malaria-infected erythrocyte using thin blood smear images

Neural computing & applications, 2018-04, Vol.29 (8), p.217-235 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2017 ;Copyright Springer Science & Business Media 2018 ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-017-2937-4

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12
Accuracy Enhanced Lung Cancer Prognosis for Improving Patient Survivability Using Proposed Gaussian Classifier System
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Accuracy Enhanced Lung Cancer Prognosis for Improving Patient Survivability Using Proposed Gaussian Classifier System

Journal of medical systems, 2019-07, Vol.43 (7), p.201-9, Article 201 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2019 ;Journal of Medical Systems is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0148-5598 ;ISSN: 1573-689X ;EISSN: 1573-689X ;DOI: 10.1007/s10916-019-1297-2 ;PMID: 31127444

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13
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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14
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 ;ISSN: 1559-0291 ;EISSN: 1559-0291 ;DOI: 10.1007/s12010-019-03093-z ;PMID: 31350666

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15
Hybrid supervised clustering based ensemble scheme for text classification
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Hybrid supervised clustering based ensemble scheme for text classification

Kybernetes, 2017-02, Vol.46 (2), p.330-348 [Peer Reviewed Journal]

Emerald Publishing Limited ;Emerald Publishing Limited 2017 ;ISSN: 0368-492X ;EISSN: 1758-7883 ;DOI: 10.1108/K-10-2016-0300

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16
On the effect of calibration in classifier combination
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On the effect of calibration in classifier combination

Applied intelligence (Dordrecht, Netherlands), 2013-06, Vol.38 (4), p.566-585 [Peer Reviewed Journal]

Springer Science+Business Media, LLC 2012 ;2015 INIST-CNRS ;Springer Science+Business Media New York 2013 ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-012-0388-2

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17
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 ;ISSN: 1573-756X ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00727-3 ;PMID: 33679210

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18
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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19
Multiple classifier system using classification confidence for texture classification
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Multiple classifier system using classification confidence for texture classification

Multimedia tools and applications, 2017-01, Vol.76 (2), p.2535-2556 [Peer Reviewed Journal]

Springer Science+Business Media New York 2016 ;Multimedia Tools and Applications is a copyright of Springer, (2016). All Rights Reserved. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-015-3231-z

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20
Robust Grape Cluster Detection in a Vineyard by Combining the AdaBoost Framework and Multiple Color Components
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Robust Grape Cluster Detection in a Vineyard by Combining the AdaBoost Framework and Multiple Color Components

Sensors (Basel, Switzerland), 2016-12, Vol.16 (12), p.2098-2098 [Peer Reviewed Journal]

Copyright MDPI AG 2016 ;2016 by the authors; licensee MDPI, Basel, Switzerland. 2016 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s16122098 ;PMID: 27973409

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