Changes in version 1.0.2.9000                      

                 Changes in version 1.0.2 (2026-02-26)                  

                        Changes in version 1.0.1                        

  - I recieved word today that the package reactablefmtr will be
    archived on 2026-03-17. I replaced the reactablefmtr functions using
    htmlwidgets and htmltools.

                 Changes in version 1.0.0 (2026-02-15)                  

  - All features are now included and working great, this is
    version 1.0.0!

                        Changes in version 0.9.0                        

  - Added stratified random sampling

                        Changes in version 0.8.6                        

  - Added German_Credit_Risk data set
  - Added extensive documentation to the Logistic function, so it's much
    easier to navigate through the code quickly.

                        Changes in version 0.8.5                        

  - Added separators
  - Removed five models which were returning errors

                        Changes in version 0.8.4                        

  - Added remove_data_correlations_greater_than, and two ways to work
    with dummy variables.

                        Changes in version 0.8.3                        

  - Corrected error in calculating binomial.

                 Changes in version 0.8.2 (2025-10-12)                  

                 Changes in version 0.6.0 (2025-08-24)                  

  - Added functions to allow setting a seed, so results are fully
    reproducible.

                 Changes in version 0.5.0 (2025-04-01)                  

                        Changes in version 0.4.0                        

                        Changes in version 0.3.0                        

                        Changes in version 0.2.0                        

                        Changes in version 0.1.0                        

  - Initial CRAN submission.

First release

  - Added South Africa heart data as a great example!

  - Added a lot of new plots to help the user choose the best possible
    model (or avoid models that are not good):

1.  Negative predictive value (free scales)
2.  Negative predictive value (fixed scales)
3.  Positive predictive value (free scales)
4.  Positive predictive value (fixed scales)
5.  F1 score, free scales
6.  F1 score, fixed scales
7.  False negative rate (free scales)
8.  False negative rate (fixed scales)
9.  False positive rate (free scales)
10. False positive rate (fixed scales)
11. True negative rate (free scales)
12. True negative rate (fixed scales)
13. True positive rate (free scales)
14. True positive rate (fixed scales)
15. Overfitting (fixed scales)
16. Variance Inflation Factor (below a level set by the user)