Nothing
ODRF: Oblique Decision Random Forest for Classification and Regression
The oblique decision tree (ODT) uses linear combinations of predictors as partitioning variables in a decision tree. Oblique Decision Random Forest (ODRF) is an ensemble of multiple ODTs generated by feature bagging. Both can be used for classification and regression as supplements to the classical CART of Breiman (1984) <DOI:10.1201/9781315139470> and Random Forest of Breiman (2001) <DOI:10.1023/A:1010933404324> respectively.
Browse package contents
Package details |
|
|---|---|
| Author | Yu Liu [aut, cre, cph], Yingcun Xia [aut] |
| Maintainer | Yu Liu <liuyuchina123@gmail.com> |
| License | GPL (>= 3) |
| Version | 0.0.4 |
| URL | https://liuyu-star.github.io/ODRF/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the ODRF package in your browser
Any scripts or data that you put into this service are public.
