A cross-validation framework, allowing for model optimization and model evaluation based on batch-wise or normal k-fold cross-validation. It is built based on the ideas in S. Guo, T. Bocklitz, et al., Analytical Methods 2017, 9 (30): 4410-4417. In applications with significant intra-group heterogeneity, the batch-wise cross-validation ensures a robust and reliable statistical modeling and model evaluation.
| Package: | rModeling |
| Type: | Package |
| Version: | 0.0.1 |
| Date: | 2020-01-23 |
| License: | GPL-2 |
| Depends: | MASS |
| caret |
The main function is crossValidation. It can be used as an independent function for model evaluation or as a wrapper of a user-defined function to optimize the parameters of a model.
S. Guo, T. Bocklitz, et al., Common mistakes in cross-validating classification models. Analytical methods 2017, 9 (30): 4410-4417.