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1
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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2
Comparing different supervised machine learning algorithms for disease prediction
Comparing different supervised machine learning algorithms for disease prediction
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Comparing different supervised machine learning algorithms for disease prediction

BMC medical informatics and decision making, 2019-12, Vol.19 (1), p.281-281, Article 281 [Peer Reviewed Journal]

COPYRIGHT 2019 BioMed Central Ltd. ;2019. 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. ;The Author(s). 2019 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-019-1004-8 ;PMID: 31864346

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3
Urban Tree Species Classification Using a WorldView-2/3 and LiDAR Data Fusion Approach and Deep Learning
Urban Tree Species Classification Using a WorldView-2/3 and LiDAR Data Fusion Approach and Deep Learning
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Urban Tree Species Classification Using a WorldView-2/3 and LiDAR Data Fusion Approach and Deep Learning

Sensors (Basel, Switzerland), 2019-03, Vol.19 (6), p.1284 [Peer Reviewed Journal]

2019 by the authors. 2019 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s19061284 ;PMID: 30875732

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4
SVM-RFE: selection and visualization of the most relevant features through non-linear kernels
SVM-RFE: selection and visualization of the most relevant features through non-linear kernels
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SVM-RFE: selection and visualization of the most relevant features through non-linear kernels

BMC bioinformatics, 2018-11, Vol.19 (1), p.432-432, Article 432 [Peer Reviewed Journal]

COPYRIGHT 2018 BioMed Central Ltd. ;cc-by (c) Sanz, Hector et al., 2018 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/3.0/es ;The Author(s). 2018 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-018-2451-4 ;PMID: 30453885

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5
Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
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Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways

PloS one, 2017-09, Vol.12 (9), p.e0184129-e0184129 [Peer Reviewed Journal]

COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Chen 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 Chen et al 2017 Chen et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0184129 ;PMID: 28873455

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6
Diagnosis by Volatile Organic Compounds in Exhaled Breath from Lung Cancer Patients Using Support Vector Machine Algorithm
Diagnosis by Volatile Organic Compounds in Exhaled Breath from Lung Cancer Patients Using Support Vector Machine Algorithm
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Diagnosis by Volatile Organic Compounds in Exhaled Breath from Lung Cancer Patients Using Support Vector Machine Algorithm

Sensors (Basel, Switzerland), 2017-02, Vol.17 (2), p.287-287 [Peer Reviewed Journal]

2017. 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/s17020287 ;PMID: 28165388

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7
Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study
Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study
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Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study

Scientific reports, 2020-10, Vol.10 (1), p.18716-18716, Article 18716 [Peer Reviewed Journal]

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. ;The Author(s) 2020 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-020-75767-2 ;PMID: 33127965

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8
Extreme learning machine-based classification of ADHD using brain structural MRI data
Extreme learning machine-based classification of ADHD using brain structural MRI data
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Extreme learning machine-based classification of ADHD using brain structural MRI data

PloS one, 2013-11, Vol.8 (11), p.e79476-e79476 [Peer Reviewed Journal]

COPYRIGHT 2013 Public Library of Science ;COPYRIGHT 2013 Public Library of Science ;2013 Peng et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/3.0/ (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. ;2013 Peng et al 2013 Peng et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0079476 ;PMID: 24260229

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9
A Novel Wearable Device for Food Intake and Physical Activity Recognition
A Novel Wearable Device for Food Intake and Physical Activity Recognition
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A Novel Wearable Device for Food Intake and Physical Activity Recognition

Sensors (Basel, Switzerland), 2016-07, Vol.16 (7), p.1067-1067 [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/s16071067 ;PMID: 27409622

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10
Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis
Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis
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Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis

Sensors (Basel, Switzerland), 2021-12, Vol.21 (24), p.8163 [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/s21248163 ;PMID: 34960257

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11
Brain Magnetic Resonance Imaging Classification Using Deep Learning Architectures with Gender and Age
Brain Magnetic Resonance Imaging Classification Using Deep Learning Architectures with Gender and Age
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Brain Magnetic Resonance Imaging Classification Using Deep Learning Architectures with Gender and Age

Sensors (Basel, Switzerland), 2022-02, Vol.22 (5), p.1766 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 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. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22051766 ;PMID: 35270913

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12
ACPred: A Computational Tool for the Prediction and Analysis of Anticancer Peptides
ACPred: A Computational Tool for the Prediction and Analysis of Anticancer Peptides
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ACPred: A Computational Tool for the Prediction and Analysis of Anticancer Peptides

Molecules (Basel, Switzerland), 2019-05, Vol.24 (10), p.1973 [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: 1420-3049 ;EISSN: 1420-3049 ;DOI: 10.3390/molecules24101973 ;PMID: 31121946

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13
Support vector machine prediction of individual Autism Diagnostic Observation Schedule (ADOS) scores based on neural responses during live eye-to-eye contact
Support vector machine prediction of individual Autism Diagnostic Observation Schedule (ADOS) scores based on neural responses during live eye-to-eye contact
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Support vector machine prediction of individual Autism Diagnostic Observation Schedule (ADOS) scores based on neural responses during live eye-to-eye contact

Scientific reports, 2024-02, Vol.14 (1), p.3232-3232 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 2024. 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. ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-024-53942-z ;PMID: 38332184

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14
Modeling of Recommendation System Based on Emotional Information and Collaborative Filtering
Modeling of Recommendation System Based on Emotional Information and Collaborative Filtering
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Modeling of Recommendation System Based on Emotional Information and Collaborative Filtering

Sensors (Basel, Switzerland), 2021-03, Vol.21 (6), p.1997 [Peer Reviewed Journal]

2021. 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. ;2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21061997 ;PMID: 33808989

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15
The "Reading the Mind in the Eyes" Test: Complete Absence of Typical Sex Difference in ~400 Men and Women with Autism
The "Reading the Mind in the Eyes" Test: Complete Absence of Typical Sex Difference in ~400 Men and Women with Autism
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The "Reading the Mind in the Eyes" Test: Complete Absence of Typical Sex Difference in ~400 Men and Women with Autism

PloS one, 2015-08, Vol.10 (8), p.e0136521-e0136521 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Baron-Cohen 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 Baron-Cohen et al 2015 Baron-Cohen et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0136521 ;PMID: 26313946

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16
PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme
PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme
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PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme

BMC bioinformatics, 2014-09, Vol.15 (1), p.311-311, Article 311 [Peer Reviewed Journal]

COPYRIGHT 2014 BioMed Central Ltd. ;2014 Li et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. ;Li et al.; licensee BioMed Central Ltd. 2014 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/1471-2105-15-311 ;PMID: 25239089

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17
A Survey on State-of-the-Art Drowsiness Detection Techniques
A Survey on State-of-the-Art Drowsiness Detection Techniques
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A Survey on State-of-the-Art Drowsiness Detection Techniques

IEEE access, 2019, Vol.7, p.61904-61919 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2019.2914373 ;CODEN: IAECCG

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18
Characterization and identification of lysine crotonylation sites based on machine learning method on both plant and mammalian
Characterization and identification of lysine crotonylation sites based on machine learning method on both plant and mammalian
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Characterization and identification of lysine crotonylation sites based on machine learning method on both plant and mammalian

Scientific reports, 2020-11, Vol.10 (1), p.20447-20447, Article 20447 [Peer Reviewed Journal]

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. ;The Author(s) 2020 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-020-77173-0 ;PMID: 33235255

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19
Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms
Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms
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Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms

Scientific reports, 2022-03, Vol.12 (1), p.3883-3883, Article 3883 [Peer Reviewed Journal]

2022. The Author(s). ;The Author(s) 2022. 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. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-07693-4 ;PMID: 35273236

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20
Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh
Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh
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Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh

Environmental challenges (Amsterdam, Netherlands), 2021-08, Vol.4, p.100084, Article 100084 [Peer Reviewed Journal]

2021 The Author(s) ;ISSN: 2667-0100 ;EISSN: 2667-0100 ;DOI: 10.1016/j.envc.2021.100084

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