2020/03/01 by Matthias Schonlau, Rosie Yuyan Zou · 6 citations
Business, Management and Accounting · Computer Science · #Financial Distress and Bankruptcy Prediction #Data Mining Algorithms and Applications #Imbalanced Data Classification Techniques
paper · pdf · doi:10.1177/1536867x20909688
openalex publication_date 2020/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Random forests (Breiman, 2001, Machine Learning 45: 5–32) is a statistical- or machine-learning algorithm for prediction. In this article, we introduce a corresponding new command, rforest. We overview the random forest algorithm and illustrate its use with two examples: The first example is a classification problem that predicts whether a credit card holder will default on his or her debt. The second example is a regression problem that predicts the logscaled number of shares of online news articles. We conclude with a discussion that summarizes key points demonstrated in the examples.