assess_multimodels: Assess multiple pairs of measured and predicted values

In philipp-baumann/simplerspec: Soil and plant spectroscopic model building and prediction

Assess multiple pairs of measured and predicted values

Description

Return performance metrics for test set predictions and measured values, e.g. for different model outcome variables.

Usage

assess_multimodels(
  data,
  ...,
  .metrics = c("simplerspec", "yardstick"),
  .model_name = "model"
)

Arguments

data	Data frame with all measured (observed) and predicted variables.
...	Multiple arguments with observed (measured)-predicted pairs, specified with dplyr::vars(o = <column_name>, p = <column_name>). Column names can strings or symbols. The arguments in ... need to be named.
.metrics	Character vector with package used for metrics calculation. Default is "simplerspec", which uses simplerspec::evaluate_model().
.model_name	String with name for the new column that specifies the model or the outcome variable. Default is "model".

Value

Data frame with with summary statistics for measured values and performance metrics for the pairs of measured and predicted values.

philipp-baumann/simplerspec documentation built on Oct. 3, 2023, 12:13 p.m.