On the role of pre and post-processing in environmental data mining
Gibert, K., Izquierdo, J., Holmes, G., Athanasiadis, I., Comas, J. & Sanchez-Marre, M. (2008). On the role of pre and post-processing in environmental data mining. In M.Sanchez-Marre, J. Bejar, J. Comas, A. Rizzoli & G. Guarisa(Eds.), Proceedings of iEMSs 2008 International Congress on Environmental Modelling and Software. (pp. 1937-1958). Barcelona, Spain: International Environmental Modelling and Software Society.
Permanent Research Commons link: https://hdl.handle.net/10289/3900
The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed.
International Environmental Modelling and Software Society
This article has been published in Proceedings of iEMSs 2008 International Congress on Environmental Modelling and Software. Used with Permission.