Predicting Soil Textural Classes Using Random Forest Models: Learning from Imbalanced Dataset

dc.contributor.author	Scholten, Thomas
dc.contributor.author	Taghizadeh-Mehrjardi, Ruhollah
dc.date.accessioned	2023-05-17T13:28:35Z
dc.date.available	2023-05-17T13:28:35Z
dc.date.issued	2022
dc.identifier.issn	2073-4395
dc.identifier.uri	http://hdl.handle.net/10900/141238
dc.language.iso	en	en
dc.publisher	Mdpi	de_DE
dc.relation.uri	http://dx.doi.org/10.3390/agronomy12112613
dc.subject.ddc	570	de_DE
dc.subject.ddc	630	de_DE
dc.subject.ddc	550	de_DE
dc.subject.ddc	610	de_DE
dc.title	Predicting Soil Textural Classes Using Random Forest Models: Learning from Imbalanced Dataset	de_DE
dc.type	Article	de_DE
utue.quellen.id	20230202000000_00652
utue.personen.roh	Mallah, Sina
utue.personen.roh	Khaki, Bahareh Delsouz
utue.personen.roh	Davatgar, Naser
utue.personen.roh	Scholten, Thomas
utue.personen.roh	Amirian-Chakan, Alireza
utue.personen.roh	Emadi, Mostafa
utue.personen.roh	Kerry, Ruth
utue.personen.roh	Mosavi, Amir Hosein
utue.personen.roh	Taghizadeh-Mehrjardi, Ruhollah
dcterms.isPartOf.ZSTitelID	Agronomy - Basel	de_DE
dcterms.isPartOf.ZS-Issue	11	de_DE
dcterms.isPartOf.ZS-Volume	12	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät