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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.8.2 |
rolling linux/jammy R-4.5 | recorder_0.8.2.tar.gz |
92.1 KiB |
0.8.2 |
rolling linux/noble R-4.5 | recorder_0.8.2.tar.gz |
92.4 KiB |
0.8.2 |
rolling source/ R- | recorder_0.8.2.tar.gz |
28.1 KiB |
0.8.2 |
latest linux/jammy R-4.5 | recorder_0.8.2.tar.gz |
92.1 KiB |
0.8.2 |
latest linux/noble R-4.5 | recorder_0.8.2.tar.gz |
92.4 KiB |
0.8.2 |
latest source/ R- | recorder_0.8.2.tar.gz |
28.1 KiB |
0.8.2 |
2026-04-26 source/ R- | recorder_0.8.2.tar.gz |
28.1 KiB |
0.8.2 |
2026-04-23 source/ R- | recorder_0.8.2.tar.gz |
28.1 KiB |
0.8.2 |
2026-04-09 windows/windows R-4.5 | recorder_0.8.2.zip |
98.6 KiB |
0.8.2 |
2025-04-20 source/ R- | recorder_0.8.2.tar.gz |
28.1 KiB |