Abstract
The accelerated growth of the environmental of information volumes on processes, phenomena and reports brings about an increasing interest in the possibility of discovering knowledge from data sets. This is a challenging task because in many cases it deals with extremely large, inherently not structured and fuzzy data, plus the presence of uncertainty. Therefore it is required to know a priori the quality of future procedures without using any additional information. For those reasons, the main goal of this paper is to define and apply new evaluation measures for decision systems by using the rough sets theory in an application of the quality assessment of the decision systems used for learning seasonal weather forecasting. The experimental studies were carried out for demonstrating the feasibility of the proposal.
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Caballero, Y., Arco, L., Bello, R., Gómez, J.M. (2007). New Measures for Evaluating Decision Systems Using Rough Set Theory: The Application in Seasonal Weather Forecasting. In: Gómez, J.M., Sonnenschein, M., Müller, M., Welsch, H., Rautenstrauch, C. (eds) Information Technologies in Environmental Engineering. Environmental Science and Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71335-7_18
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DOI: https://doi.org/10.1007/978-3-540-71335-7_18
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