% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plotting_utils.R
\name{plot_tuning_results}
\alias{plot_tuning_results}
\title{Plotting Tuner Search Results}
\usage{
plot_tuning_results(analysis_object)
}
\arguments{
\item{analysis_object}{Fitted analysis_object with 'fine_tuning()'.}
}
\value{
analysis_object
}
\description{
The \strong{plot_tuning_results()} function Visualizes hyperparameter optimization
search results adapting output format to the optimization methodology
employed. For Bayesian Optimization: displays iteration-by-iteration loss
function evolution across iterations, acquisition function values guiding
sequential hyperparameter sampling, and final hyperparameter configuration
with cross-validation performance metrics. For Grid Search: displays
performance surfaces across hyperparameter dimensions and rank-ordered
configurations by validation performance.
}
\examples{
# Note: For obtaining the plot with tuning results the user needs to
# complete till fine_tuning( ) function of the MLwrap pipeline.
# See the full pipeline example under table_best_hyperparameters()
# Final call signature:
# plot_tuning_results(wrap_object)
}
\seealso{
\code{\link{table_best_hyperparameters}}
}
