calculate_rroc {tidyhte} | R Documentation |
Regression ROC Curve calculation
Description
This function calculates the RegressionROC Curve of of Hernández-Orallo doi:10.1016/j.patcog.2013.06.014. It provides estimates for the positive and negative errors when predictions are shifted by a variety of constants (which range across the domain of observed residuals). Curves closer to the axes are, in general, to be preferred. In general, this curve provides a simple way to visualize the error properties of a regression model.
Usage
calculate_rroc(label, prediction, nbins = 100)
Arguments
label |
True label |
prediction |
Model prediction of the label (out of sample) |
nbins |
Number of shift values to sweep over |
Details
The dot shows the errors when no shift is applied, corresponding to the base model predictions.
Value
A tibble with nbins
rows.
References
Hernández-Orallo, J. (2013). ROC curves for regression. Pattern Recognition, 46(12), 3395-3411.
[Package tidyhte version 1.0.2 Index]