Create a plot for a neural network model

The function draws a neural network plot as a neural interpretation diagram using with the plotnet function of the NeuralNetTools R package.

nplot(dnn.fit, bias = FALSE, ...)

Arguments

dnn.fit

A neural network model from cito R package.

bias

A logical value, indicating whether to draw biases in the layers (default = FALSE).

...

Currently ignored.

Value

The function invisibly returns the graphical object representing the neural network architecture designed by NeuralNetTools.

Details

The induced subgraph of the input graph mapped on data variables. Based on the estimated connection weights, if the connection weight W > 0, the connection is activated and it is highlighted in red; if W < 0, the connection is inhibited and it is highlighted in blue.

References

Beck, M.W. 2018. NeuralNetTools: Visualization and Analysis Tools for Neural Networks. Journal of Statistical Software. 85(11):1-20.

Author

Mario Grassi mario.grassi@unipv.it

Examples

# \donttest{
if (torch::torch_is_installed()){

# load ALS data
ig<- alsData$graph
data<- alsData$exprs
data<- transformData(data)$data

#ncores<- parallel::detectCores(logical = FALSE)
dnn0 <- SEMdnn(ig, data, train=1:nrow(data), grad = FALSE,
      #hidden = 5*K, link = "selu", bias = TRUE,
      hidden = c(10, 10, 10), link = "selu", bias =TRUE,
      validation = 0, epochs = 32, ncores = 2)

 for (j in 1:length(dnn0$model)) {
   nnj <- dnn0$model[[j]][[1]]
   nplot(nnj)
   Sys.sleep(5)
 }
}
#> Conducting the nonparanormal transformation via shrunkun ECDF...done.
#> Running SEM model via DNN...
#>  done.
#> 
#> DNN solver ended normally after 736 iterations
#> 
#>  logL:-49.960691  srmr:0.2183

# }