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Which method to use? An assessment of data mining methods in Environmental Data Science

Author
Gibert, Karina; Izquierdo, J.; Sànchez-Marrè, M.; Hamilton, S.; Rodriguez-Roda, I.; Holmes, G.
Type of activity
Journal article
Journal
Environmental modelling & software
Date of publication
2018-12
Volume
110
First page
3
Last page
27
DOI
10.1016/j.envsoft.2018.09.021
Repository
http://hdl.handle.net/2117/133895 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S1364815218308715 Open in new window
Abstract
Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reaso...
Keywords
Data mining, Data science, Environmental systems, Method selection, Multidisciplinarity
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
KEMLG - Knowledge Engineering and Machine Learning Group

Participants

  • Gibert, Karina  (author)
  • Izquierdo Sebastián, Joaquín  (author)
  • Sànchez Marrè, Miquel  (author)
  • Hamilton, Serena H.  (author)
  • Rodriguez Roda, Ignasi  (author)
  • Holmes, Geoffrey  (author)