vtreat
A Statistically Sound 'data.frame' Processor/Conditioner
A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. 'vtreat' prepares variables so that data has fewer exceptional cases, making it easier to safely use models in production. Common problems 'vtreat' defends against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new categorical levels (levels seen during application, but not during training). Reference: "'vtreat': a data.frame Processor for Predictive Modeling", Zumel, Mount, 2016, doi:10.5281/zenodo.1173313.
- Version1.6.5
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release06/12/2024
Documentation
- VignetteMulti Class vtreat
- VignetteSaving Treatment Plans
- Vignettevtreat Variable Importance
- Vignettevtreat package
- Vignettevtreat cross frames
- Vignettevtreat grouping example
- Vignettevtreat overfit
- Vignettevtreat Rare Levels
- Vignettevtreat scale mode
- Vignettevtreat significance
- Vignettevtreat data splitting
- VignetteVariable Types
- Vignettevtreat Formal Article
- MaterialREADME
- MaterialNEWS
Team
John Mount
Nina Zumel
Show author detailsRolesAuthorWin-Vector LLC
Show author detailsRolesCopyright holder
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
- Depends1 package
- Imports1 package
- Suggests9 packages
- Reverse Imports1 package
- Reverse Suggests1 package