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  • Molecular Diversity Preservation International  (2)
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  • 1
    Publication Date: 2019-09-07
    Description: Field experiments were performed for two growing seasons in Spain under Mediterranean conditions to evaluate the response of onion growth, plant water status, bulb yield, irrigation water use efficiency (IWUE), and gross revenue to regulated deficit irrigation strategies (RDI). Seven irrigation treatments were utilized, including the application of 100% irrigation water requirements (IWR) during the entire growing season and the application of 75% or 50% of the IWR during one of the following growth stages: the vegetative growth, bulbing, and bulb ripening stages. The deficit irrigation strategies tested decreased marketable yields to greater or lesser extents; therefore, if water is readily available, full irrigation would be recommended. The RDI with 50% of the IWR during the bulb ripening stage led to important water savings (22%) and to slight decreases in yield (9%), improving IWUE (20%) compared with full irrigation, and this strategy can be recommended under a severe water shortage. A satisfactory bulb yield was obtained with RDI with 75% of the IWR during the bulb ripening stages, resulting in a lower reduction in yield (4%) and in an increased IWUE (9%); this strategy is an advisable strategy for onion production under a mild water shortage in Mediterranean conditions.
    Electronic ISSN: 2073-4395
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 2
    Publication Date: 2021-08-10
    Description: The term credit scoring refers to the application of formal statistical tools to support or automate loan-issuing decision-making processes. One of the most extended methodologies for credit scoring include fitting logistic regression models by using WOE explanatory variables, which are obtained through the discretization of the original inputs by means of classification trees. However, this Weight of Evidence (WOE)-based methodology encounters some difficulties in order to model interactions between explanatory variables. In this paper, an extension of the WOE-based methodology for credit scoring is proposed that allows constructing a new kind of WOE variable devised to capture interaction effects. Particularly, these new WOE variables are obtained through the simultaneous discretization of pairs of explanatory variables in a single classification tree. Moreover, the proposed extension of the WOE-based methodology can be complemented as usual by balance scorecards, which enable explaining why individual loans are granted or not granted from the fitted logistic models. Such explainability of loan decisions is essential for credit scoring and even more so by taking into account the recent law developments, e.g., the European Union’s GDPR. An extensive computational study shows the feasibility of the proposed approach that also enables the improvement of the predicitve capability of the standard WOE-based methodology.
    Electronic ISSN: 2227-7390
    Topics: Mathematics
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