dc.contributor.advisor | Langseth, Helge | nb_NO |
dc.contributor.advisor | Husebø, Tore Anders | nb_NO |
dc.contributor.author | Gogstad, Jostein | nb_NO |
dc.contributor.author | Øysæd, Jostein | nb_NO |
dc.date.accessioned | 2014-12-19T13:33:58Z | |
dc.date.available | 2014-12-19T13:33:58Z | |
dc.date.created | 2010-09-04 | nb_NO |
dc.date.issued | 2009 | nb_NO |
dc.identifier | 348791 | nb_NO |
dc.identifier | ntnudaim:4835 | nb_NO |
dc.identifier.uri | http://hdl.handle.net/11250/251355 | |
dc.description.abstract | The tax history of a company is used to predict corporate bankruptcies using Bayesian inference. Our developed model uses a combination of Naive Bayesian classification and Gaussian Processes. Based on a sample of 1184 companies, we conclude that the Naive Bayes-Gaussian Process model successfully forecasts corporate bankruptcies with high accuracy. A comparison is performed with the current system in place at one of the largest banks in Norway. We present evidence that our classification model, based solely on tax data, is better than the model currently in place. | nb_NO |
dc.language | eng | nb_NO |
dc.publisher | Institutt for datateknikk og informasjonsvitenskap | nb_NO |
dc.subject | ntnudaim | no_NO |
dc.subject | SIF2 datateknikk | no_NO |
dc.subject | Intelligente systemer | no_NO |
dc.title | Early Warnings of Corporate Bankruptcies Using Machine Learning Techniques | nb_NO |
dc.type | Master thesis | nb_NO |
dc.source.pagenumber | 115 | nb_NO |
dc.contributor.department | Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskap | nb_NO |