Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/51199
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dc.contributor.authorAlaminos, David-
dc.contributor.authorFernández, Sergio M.-
dc.contributor.authorNeves, Paulo Magalhães-
dc.contributor.authorSantos, José António C-
dc.date.accessioned2019-11-01T10:36:09Z-
dc.date.available2019-11-01T10:36:09Z-
dc.date.issued2019-11-
dc.identifier.issn0975-1084 (Online); 0022-4456 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/51199-
dc.description733-737en_US
dc.description.abstractConsidering the great capacity of data mining techniques to extract useful information from large databases and to manage heterogeneous variables, this paper uses Fuzzy C4.5 Decision Trees for the prediction of sovereign debt crises. To this end, prediction models have been constructed for different regions, and another global model for the whole world. The results obtained show that Fuzzy C4.5 Decision Trees method overcomes the predictive power of existing models in the previous literature and provides more explanatory information on the reasons that cause sovereign debt crises.en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceJSIR Vol.78(11) [November 2019]en_US
dc.subjectSovereign debt crisisen_US
dc.subjectC4.5 algorithmen_US
dc.subjectFuzzy decision treesen_US
dc.subjectDefault predictionen_US
dc.titlePredicting Sovereign Debt Crises with Fuzzy Decision Treesen_US
dc.typeArticleen_US
Appears in Collections:JSIR Vol.78(11) [November 2019]

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