Robustness analysis of machine learning classifiers in predicting spatial gully erosion susceptibility with altered training samples

Hembram, TK; Saha, S; Pradhan, B; Abdul Maulud, KN; Alamri, AM

Robustness analysis of machine learning classifiers in predicting spatial gully erosion susceptibility with altered training samples

Hembram, TK Saha, S Pradhan, B

Abdul Maulud, KN Alamri, AM

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Publisher:: TAYLOR & FRANCIS LTD
Publication Type:: Journal Article
Citation:: Geomatics Natural Hazards and Risk, 2021, 12, (1), pp. 794-828
Issue Date:: 2021-01-01

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Field	Value	Language
dc.contributor.advisor	“This is an Accepted Manuscript of an article published by Taylor & Francis in [Geomatics Natural Hazards and Risk, 2021, 12, (1), pp. 794-828], available online: https://www.tandfonline.com/doi/full/10.1080/19475705.2021.1890644]”
dc.contributor.author	Hembram, TK
dc.contributor.author	Saha, S
dc.contributor.author	Pradhan, B https://orcid.org/0000-0001-9863-2054
dc.contributor.author	Abdul Maulud, KN
dc.contributor.author	Alamri, AM
dc.date.accessioned	2021-05-05T00:54:59Z
dc.date.available	2021-05-05T00:54:59Z
dc.date.issued	2021-01-01
dc.identifier.citation	Geomatics Natural Hazards and Risk, 2021, 12, (1), pp. 794-828
dc.identifier.issn	1947-5705
dc.identifier.issn	1947-5713
dc.identifier.uri	http://hdl.handle.net/10453/148655
dc.language	English
dc.publisher	TAYLOR & FRANCIS LTD
dc.relation.ispartof	Geomatics Natural Hazards and Risk
dc.relation.isbasedon	10.1080/19475705.2021.1890644
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0406 Physical Geography and Environmental Geoscience
dc.title	Robustness analysis of machine learning classifiers in predicting spatial gully erosion susceptibility with altered training samples
dc.type	Journal Article
utslib.citation.volume	12
utslib.for	0406 Physical Geography and Environmental Geoscience
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	open_access	*
dc.date.updated	2021-05-05T00:54:58Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	12
utslib.citation.issue	1

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http://hdl.handle.net/10453/148655