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1
Two-Stage Hybrid Data Classifiers Based on SVM and kNN Algorithms
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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2
GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms
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
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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4
Multiple classifier system for remote sensing image classification: a review
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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5
Enhanced Face Detection Technique Based on Color Correction Approach and SMQT Features
Enhanced Face Detection Technique Based on Color Correction Approach and SMQT Features
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Enhanced Face Detection Technique Based on Color Correction Approach and SMQT Features

Journal of software engineering and applications, 2013-10, Vol.6 (10), p.519-525

ISSN: 1945-3116 ;EISSN: 1945-3124 ;DOI: 10.4236/jsea.2013.610062

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6
A hybrid hierarchical framework for classification of breast density using digitized film screen mammograms
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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7
Distance classifier ensemble based on intra-class and inter-class scatter
Distance classifier ensemble based on intra-class and inter-class scatter
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Conference Proceeding 		Add to My Research

Distance classifier ensemble based on intra-class and inter-class scatter

E3S Web of Conferences, 2022, Vol.360, p.1041 [Peer Reviewed Journal]

2022. This work is licensed 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: 2267-1242 ;ISSN: 2555-0403 ;EISSN: 2267-1242 ;DOI: 10.1051/e3sconf/202236001041

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8
Prediction of Skin Disease Using Ensemble Data Mining Techniques and Feature Selection Method—a Comparative Study
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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9
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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10
Dementia classification using MR imaging and clinical data with voting based machine learning models
Dementia classification using MR imaging and clinical data with voting based machine learning models
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Article 		Add to My Research

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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11
Discrimination of Mine Seismic Events and Blasts Using the Fisher Classifier, Naive Bayesian Classifier and Logistic Regression
Discrimination of Mine Seismic Events and Blasts Using the Fisher Classifier, Naive Bayesian Classifier and Logistic Regression
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Article 		Add to My Research

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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12
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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Article 		Add to My Research

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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13
Machine learning classification can reduce false positives in structure-based virtual screening
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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14
Fusion and Classification of SAR and Optical Data Using Multi-Image Color Components with Differential Gradients
Fusion and Classification of SAR and Optical Data Using Multi-Image Color Components with Differential Gradients
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Article 		Add to My Research

Fusion and Classification of SAR and Optical Data Using Multi-Image Color Components with Differential Gradients

Remote sensing (Basel, Switzerland), 2023-01, Vol.15 (1), p.274 [Peer Reviewed Journal]

2023 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/rs15010274

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15
Fabric Defect Detection Using a One-class Classification Based on Depthwise Separable Convolution Autoencoder
Fabric Defect Detection Using a One-class Classification Based on Depthwise Separable Convolution Autoencoder
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Fabric Defect Detection Using a One-class Classification Based on Depthwise Separable Convolution Autoencoder

Journal of physics. Conference series, 2023-08, Vol.2562 (1), p.12053 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;Published under licence by IOP Publishing Ltd. 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: 10.1088/1742-6596/2562/1/012053

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16
Risk-averse classification
Risk-averse classification
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Risk-averse classification

Annals of operations research, 2019-08, p.1-35 [Peer Reviewed Journal]

Annals of Operations Research is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0254-5330 ;EISSN: 1572-9338 ;DOI: 10.1007/s10479-019-03344-6

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17
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
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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18
Simple and Effective Complementary Label Learning Based on Mean Square Error Loss
Simple and Effective Complementary Label Learning Based on Mean Square Error Loss
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Simple and Effective Complementary Label Learning Based on Mean Square Error Loss

Journal of physics. Conference series, 2023-05, Vol.2504 (1), p.12016 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;Published under licence by IOP Publishing Ltd. 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: 10.1088/1742-6596/2504/1/012016

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19
Diabetes Prediction Using Ensembling of Different Machine Learning Classifiers
Diabetes Prediction Using Ensembling of Different Machine Learning Classifiers
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Article 		Add to My Research

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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20
TSE-IDS: A Two-Stage Classifier Ensemble for Intelligent Anomaly-Based Intrusion Detection System
TSE-IDS: A Two-Stage Classifier Ensemble for Intelligent Anomaly-Based Intrusion Detection System
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Article 		Add to My Research

TSE-IDS: A Two-Stage Classifier Ensemble for Intelligent Anomaly-Based Intrusion Detection System

IEEE access, 2019, Vol.7, p.94497-94507 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2019.2928048 ;CODEN: IAECCG

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