We study the performances of various predictive models including decision trees, random forests, neural networks, and linear discriminant analysis on an imbalanced data set of home loan applications. During the process, we propose our undersampling algorithm to cope with the issues created by...

We identify a set of “rules of thumb” that characterise economic, financial and structural conditions preceding the onset of banking and currency crises in 36 advanced economies over 1970–2010. We use the Classification and Regression Tree methodology (CART) and its Random Forest (RF)...

We identify a set of "rules of thumb" that characterise economic, financial and structural conditions preceding the onset of banking and currency crises in 36 advanced economies over 1970–2010. We use the Classification and Regression Tree methodology (CART) and its Random Forest (RF)...