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). 'vtreat::prepare' should be used as you would use 'model.matrix'.
Maintainer: John Mount jmount@win-vector.com
Authors:
Nina Zumel nzumel@win-vector.com
Other contributors:
Win-Vector LLC [copyright holder]
For more information:
vignette(package='vtreat')
Website: https://github.com/WinVector/vtreat
Useful links: