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Calculate Training Error for Machine Learning Models
get_training_error.Rd
Computes the training error for a given machine learning model using resampled datasets. This function is designed to fit the model to each split of the data, predict outcomes, and calculate a performance metric (e.g., R-squared) for each resample.
Arguments
- model
A machine learning model object compatible with the
fit_resamples
method.- splits
An object containing data splits, typically generated by functions from the
rsample
package, used for resampling.- metric
The performance metric of interest as a string.
Value
A data frame containing the performance metric (R-squared by default) for each resample and an identification of the error type as "Training".
Examples
if (FALSE) {
library(tidymodels) # assuming tidymodels includes necessary packages
data(iris)
model <- linear_reg() |> set_engine("lm")
splits <- initial_split(iris, prop = 0.75)
training_error <- get_training_error(model, splits)
}