% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plotting_utils.R
\name{plot_graph_nn}
\alias{plot_graph_nn}
\title{Plot Neural Network Architecture}
\usage{
plot_graph_nn(analysis_object)
}
\arguments{
\item{analysis_object}{Fitted analysis_object with 'fine_tuning()'.}
}
\value{
analysis_object
}
\description{
Renders a directed acyclic graph representation of Neural Network
architecture showing layer stacking order, layer-specific dimensions
(neurons per layer), activation functions applied at each layer, and
optimized hyperparameter values (learning rate, batch size, dropout rates,
regularization coefficients) obtained from hyperparameter tuning procedures.
}
\examples{
# Note: For obtaining the Neural Network architecture graph 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_graph_nn(wrap_object)
}
\seealso{
\code{\link{table_best_hyperparameters}}
}
