recorder: 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.

Version: 0.8.2
Depends: R (≥ 3.4.0)
Imports: data.table, crayon
Suggests: testthat, knitr, rmarkdown
Published: 2019-06-13
DOI: 10.32614/CRAN.package.recorder
Author: Lars Kjeldgaard [aut, cre]
Maintainer: Lars Kjeldgaard <lars_kjeldgaard at>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: recorder results


Reference manual: recorder.pdf
Vignettes: Introduction to recorder


Package source: recorder_0.8.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): recorder_0.8.2.tgz, r-oldrel (arm64): recorder_0.8.2.tgz, r-release (x86_64): recorder_0.8.2.tgz, r-oldrel (x86_64): recorder_0.8.2.tgz
Old sources: recorder archive


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