loss_score_ranking: Ranks tuning parameters according to loss functions

In autoMrP: Improving MrP with Ensemble Learning

Ranks tuning parameters according to loss functions

Description

loss_score_ranking() ranks tuning parameters according to the scores received in multiple loss functions.

Usage

loss_score_ranking(score, loss.fun)

Arguments

score	A data set containing loss function names, the loss function values, and the tuning parameter values.
loss.fun	Loss function. A character-valued scalar indicating whether prediction loss should be measured by the mean squared error (MSE) or the mean absolute error (MAE). Default is MSE.

Value

Returns a tibble containing the parameter grid as well as a rank column that corresponds to the cross-validation rank of a parameter combination across all loss function scores.

autoMrP documentation built on Aug. 17, 2023, 5:07 p.m.