Nothing
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.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Lars Kjeldgaard [aut, cre] |
| Maintainer | Lars Kjeldgaard <lars_kjeldgaard@hotmail.com> |
| License | MIT + file LICENSE |
| Version | 0.8.2 |
| URL | https://github.com/smaakage85/recorder |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the recorder package in your browser
Any scripts or data that you put into this service are public.
