Improving prediction accuracy for acid sulfate soil mapping by means of variable selection

V Estévez; S Mattbäck; A Boman; A Beucher; KM Björk; P Österholm

doi:10.3389/fenvs.2023.1213069

Improving prediction accuracy for acid sulfate soil mapping by means of variable selection

V Estévez, S Mattbäck, A Boman, A Beucher, KM Björk, P Österholm

Geology and Mineralogy

Research output: Contribution to journal › Article › Scientific › peer-review

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Original language	English
Article number	1213069
Number of pages	15
Journal	Frontiers in Environmental Science
Volume	11
DOIs	https://doi.org/10.3389/fenvs.2023.1213069
Publication status	Published - 14 Jul 2023
MoE publication type	A1 Journal article-refereed

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10.3389/fenvs.2023.1213069

fenvs-11-1213069Final published version, 2.82 MBLicence: CC BY

https://urn.fi/URN:NBN:fi-fe202402086233

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title = "Improving prediction accuracy for acid sulfate soil mapping by means of variable selection",

keywords = "Acid sulfate soils, Digital soil mapping, Gradient boosting, Machine learning, Random forest, Variable selection",

author = "V Est{\'e}vez and S Mattb{\"a}ck and A Boman and A Beucher and KM Bj{\"o}rk and P {\"O}sterholm",

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language = "English",

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T1 - Improving prediction accuracy for acid sulfate soil mapping by means of variable selection

AU - Estévez, V

AU - Mattbäck, S

AU - Boman, A

AU - Beucher, A

AU - Björk, KM

AU - Österholm, P

PY - 2023/7/14

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KW - Acid sulfate soils

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KW - Gradient boosting

KW - Machine learning

KW - Random forest

KW - Variable selection

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DO - 10.3389/fenvs.2023.1213069

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VL - 11

JO - Frontiers in Environmental Science

JF - Frontiers in Environmental Science

M1 - 1213069

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Improving prediction accuracy for acid sulfate soil mapping by means of variable selection

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