Effect of hyperparameters on variable selection in random forests
<p>These are data used to generate the results presented in simulation studies conducted in Fouodo et al. 2023. Each dataset is an R object in RDS format with 100 lists. For each element of the list, parameters used to generate the data are presented, followed by the simulated data. <a href="https://github.com/imbs-hl/RF-hyperparameters-and-variable-selection">Here</a> is the git repository of the R code used to conduct simulations in the manuscript. The files <a href="https://github.com/imbs-hl/RF-hyperparameters-and-variable-selection/tree/main/R-code/01-scenario1">01-data-only.R</a> and <a href="https://github.com/imbs-hl/RF-hyperparameters-and-variable-selection/tree/main/R-code/02-scenario2">02-data-only.R</a> contain the functions and more details about how the data have been simulated for studies 1 and 2.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 4
Topics
Dataset details
- Repository
- zenodo
- Published
- August 31, 2023
- License
- cc-by-4.0
- DOI
- 10.5281/zenodo.8308234
Scored with release 0.9.0
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