% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plotting_utils.R
\name{plot_loss_curve}
\alias{plot_loss_curve}
\title{Plot Neural Network Loss Curve}
\usage{
plot_loss_curve(analysis_object)
}
\arguments{
\item{analysis_object}{Fitted analysis_object with 'fine_tuning()'.}
}
\value{
analysis_object
}
\description{
Displays training loss trajectory computed on the validation set across
training epochs. Enables visual diagnosis of convergence dynamics,
identification of appropriate early stopping points, detection of overfitting
patterns (where validation loss increases while training loss decreases), and
assessment of optimization stability throughout the training process.
}
\examples{
# Note: For obtaining the loss curve plot the user needs to
# complete till the fine_tuning( ) function of the MLwrap pipeline.
# See the full pipeline example under table_best_hyperparameters()
# (Neural Network engine required)
# Final call signature:
# plot_loss_curve(wrap_object)
}
\seealso{
\code{\link{table_best_hyperparameters}}
}
