logicDT
Identifying Interactions Between Binary Predictors
A statistical learning method that tries to find the best set of predictors and interactions between predictors for modeling binary or quantitative response data in a decision tree. Several search algorithms and ensembling techniques are implemented allowing for finetuning the method to the specific problem. Interactions with quantitative covariables can be properly taken into account by fitting local regression models. Moreover, a variable importance measure for assessing marginal and interaction effects is provided. Implements the procedures proposed by Lau et al. (2024, doi:10.1007/s10994-023-06488-6).
- Version1.0.5
- R versionunknown
- LicenseMIT
- Needs compilation?Yes
- Last release09/23/2024
Documentation
Team
Michael Lau
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package