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.
- Version0.0.4
- R version≥ 3.5.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Languageen-US
- ODRF citation info
- Last release05/28/2023
Documentation
Team
Yu Liu
Yingcun Xia
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Insights
Last 30 days
This package has been downloaded 211 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 11 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,572 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 27 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Depends1 package
- Imports9 packages
- Suggests4 packages
- Linking To2 packages