Machine learning and processing of large data

Nussbaum, Madlene (2022). Machine learning and processing of large data In: Reference Module in Earth Systems and Environmental Sciences (pp. 509-520). Amsterdam, Netherlands: Elsevier 10.1016/B978-0-12-822974-3.00065-3

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Machine learning refers to a set of tools to establish models of linear or non-linear relations or other previously unknown relationships in complex data. In soil science it is widely used to create soil maps, to derive difficult to measure soil properties from sensor data or to provide information for soil related decision-making in agriculture. Machine learning algorithms based on decision trees are among the most popular techniques. Models with good predictive power are complex, but often outperform simpler models from classical statistics. Interpretation with algorithms that subsequently analyze the models is possible yet challenging.

Item Type:	Book Section (Encyclopedia Article)
Division/Institute:	School of Agricultural, Forest and Food Sciences HAFL School of Agricultural, Forest and Food Sciences HAFL > Agriculture School of Agricultural, Forest and Food Sciences HAFL > Agriculture > Soils and Geoinformation
Name:	Nussbaum, Madlene0000-0002-6808-8956
Subjects:	L Education > LT Textbooks Q Science > Q Science (General) S Agriculture > S Agriculture (General)
ISBN:	9780124095489
Publisher:	Elsevier
Language:	English
Submitter:	Madlene Nussbaum
Date Deposited:	02 Nov 2022 09:40
Last Modified:	13 Aug 2023 01:37
Publisher DOI:	10.1016/B978-0-12-822974-3.00065-3
ARBOR DOI:	10.24451/arbor.17884
URI:	https://arbor.bfh.ch/id/eprint/17884