recorder (0.8.2)

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Toolkit to Validate New Data for a Predictive Model.

A lightweight toolkit to validate new observations when computing their predictions with a predictive model. The validation process consists of two steps: (1) record relevant statistics and meta data of the variables in the original training data for the predictive model and (2) use these data to run a set of basic validation tests on the new set of observations.

Maintainer: Lars Kjeldgaard
Author(s): Lars Kjeldgaard [aut, cre]

License: MIT + file LICENSE

Uses: crayon, data.table, testthat, knitr, rmarkdown

Released 10 months ago.

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