rModeling-package: Cross-validation in spectroscopic data

In rModeling: A Framework of Cross-Validation

Description

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.

Details

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.

Author(s)

Shuxia Guo, Thomas Bocklitz, Juergen Popp

Maintainer: Shuxia Guo<[e-mail]>, Thomas Bocklitz<[e-mail]>, Juergen Popp<[e-mail]>

References

S. Guo, T. Bocklitz, et al., Common mistakes in cross-validating classification models. Analytical methods 2017, 9 (30): 4410-4417.

rModeling documentation built on March 26, 2020, 7:48 p.m.