predSummary

reference

prediction

a vector of character, specifying the group names. Ignored if <code>classify=FALSE</code>.

a boolean value, telling whether a classification or regression task.

classify

produce the confusion matrix using function <code><a rd-options="caret" href="/link/confusionMatrix?package=rModeling&version=0.0.3&to=caret" data-mini-rdoc="caret::confusionMatrix">confusionMatrix</a></code> from package caret if <code>classify=TRUE</code>, otherwise calculate the RMSE between the predicted and groundtruth values.

A framework of cross-validation for spectral data analysis that allows for automatic tuning of model parameters and for model evaluation. It is particularly useful for applications where intra-group heterogeneity is significant due to inter individual differences. S. Guo, T. Bocklitz, U. Neugebauer, J.Popp (2017) <doi:10.1039/C7AY01363A>.

Shuxia Guo

rModeling

A Framework of Cross-Validation

Thomas Bocklitz

Juergen Popp

predSummary function

produce the confusion matrix using function <code><a rd-options='caret' href='confusionMatrix'>confusionMatrix</a></code> from package caret if <code>classify=TRUE</code>, otherwise calculate the RMSE between the predicted and groundtruth values.

predSummary: Calculate the merit of the prediction

Description

Usage

Arguments

Value

See Also