ماجستير
2017 موثق
Machine Learning Methods for Credit Risk Modelling
الملخص
This master's thesis is divided into three parts. In the first part I described P2P lending, its characteristics, basic concepts and practical implications. I also compared P2P market in the Czech Republic, UK and USA. The second part consists of theoretical basics for chosen methods of machine learning, which are naive bayes classifier, classification tree, random forest and logistic regression. I also described methods to evaluate the quality of classification models listed above. The third part is a practical one and shows the complete workflow of creating classification model, from data preparation to evaluation of model.
الكلمات المفتاحية
غير متوفر
التخصصات
رسائل وأطاريح مشابهة
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- Developing and Evaluating Fairness-Aware Machine Learning Methods; Ethical Responsibility and Accountability for Algorithmic Bias in Hiring Tim Wang · 2026
- Machine Learning Methods for Time Series Forecasting-E-commerce Sales Study Case Ana Rita Mendes Teixeira · 2023
- Domain independence of Machine Learning and lexicon based methods in sentiment analysis. Meriton Xhymshiti · 2020
