Package: recorder 0.8.2
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.
Authors:
recorder_0.8.2.tar.gz
recorder_0.8.2.zip(r-4.5)recorder_0.8.2.zip(r-4.4)recorder_0.8.2.zip(r-4.3)
recorder_0.8.2.tgz(r-4.4-any)recorder_0.8.2.tgz(r-4.3-any)
recorder_0.8.2.tar.gz(r-4.5-noble)recorder_0.8.2.tar.gz(r-4.4-noble)
recorder_0.8.2.tgz(r-4.4-emscripten)recorder_0.8.2.tgz(r-4.3-emscripten)
recorder.pdf |recorder.html✨
recorder/json (API)
# Install 'recorder' in R: |
install.packages('recorder', repos = c('https://smaakage85.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/smaakage85/recorder/issues
- iris_newdata - Simulated Iris New Data
data-analysismachine-learningpredictive-analyticspredictive-modeling
Last updated 5 years agofrom:13680fa8df. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 09 2024 |
R-4.5-win | OK | Oct 09 2024 |
R-4.5-linux | OK | Oct 09 2024 |
R-4.4-win | OK | Oct 09 2024 |
R-4.4-mac | OK | Oct 09 2024 |
R-4.3-win | OK | Oct 09 2024 |
R-4.3-mac | OK | Oct 09 2024 |
Exports:create_tests_meta_dataget_clean_rowsget_failed_testsget_failed_tests_stringget_tests_meta_dataplayrecordrun_validation_tests
Dependencies:crayondata.table