Semantic Scholar
Open Access
2020
943 sitasi
The random forest algorithm for statistical learning
Matthias Schonlau
Rosie Yuyan Zou
Abstrak
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.
Topik & Kata Kunci
Penulis (2)
M
Matthias Schonlau
R
Rosie Yuyan Zou
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2020
- Bahasa
- en
- Total Sitasi
- 943×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1177/1536867X20909688
- Akses
- Open Access ✓