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The random forest algorithm for statistical learning

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Abstract & Overview

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.

Cite this record

Matthias Schonlau, Rosie Yuyan Zou (2020). The random forest algorithm for statistical learning. The Stata Journal Promoting communications on statistics and Stata, 20(1), 3–29. https://doi.org/10.1177/1536867x20909688

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Schonlau, M., & Zou, R. Y. (2020). The random forest algorithm for statistical learning. The Stata Journal Promoting communications on statistics and Stata, 20(1), 3–29. https://doi.org/10.1177/1536867x20909688
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