Credit Risk Evaluation using Machine Learning
In this thesis, we examine the machine learning models logistic regression, multilayer perceptron and random forests in the purpose of discriminate between good and bad credit applicants. In addition to these models we address the problem of imbalanced data with the Synthetic Minority Over-Sampling...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Statistik och maskininlärning
2017
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138968 |