Exploring the novel support points-based split method on a soil dataset
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F21%3A85643" target="_blank" >RIV/60460709:41210/21:85643 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.measurement.2021.110131" target="_blank" >https://doi.org/10.1016/j.measurement.2021.110131</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.measurement.2021.110131" target="_blank" >10.1016/j.measurement.2021.110131</a>
Alternative languages
Result language
angličtina
Original language name
Exploring the novel support points-based split method on a soil dataset
Original language description
Data splitting is an integral step in machine learning that ensures good model generalization. The novel support points based split method has been evaluated on several datasets and has shown to be promising than conventional methods . However, this method has never been applied in soil based research. Therefore, the current study compared soil organic carbon RMSE prediction results generated through the conventional random split and the novel support points-based split methods.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
40104 - Soil science
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
MEASUREMENT
ISSN
0263-2241
e-ISSN
1873-412X
Volume of the periodical
186
Issue of the periodical within the volume
dec
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
4
Pages from-to
0-0
UT code for WoS article
000704917600005
EID of the result in the Scopus database
2-s2.0-85114701866