title: Plotting neural network model from nnet package R cran
body: <p>Is there any package or other software to plot neural network models from the nnet package cran.</p>
  
  <p>I trained a neural network model (3 inputs and 1 output) using nnet and Rattle:</p>
  
  <pre><code>crs$nnet &lt;- nnet(as.factor(Target) ~ .,
                   data=crs$dataset[crs$sample,c(crs$input, crs$target)],
                   size=10, skip=TRUE, MaxNWts=10000, 
                   trace=FALSE, maxit=100)
  </code></pre>
  
  <p>This was the summary of the model :</p>
  
  <pre><code>Neural Network build options: skip-layer connections; entropy fitting.
  
  In the following table:
     b  represents the bias associated with a node
     h1 represents hidden layer node 1
     i1 represents input node 1 (i.e., input variable 1)
     o  represents the output node
  
  Weights for node h1:
   b-&gt;h1 i1-&gt;h1 i2-&gt;h1 i3-&gt;h1 
   -0.66   0.15   0.24  -0.31 
  
  Weights for node h2:
   b-&gt;h2 i1-&gt;h2 i2-&gt;h2 i3-&gt;h2 
   -0.62   1.32   1.16   0.24 
  
  Weights for node h3:
   b-&gt;h3 i1-&gt;h3 i2-&gt;h3 i3-&gt;h3 
   13.59 -10.44   0.78  -6.46 
  
  Weights for node h4:
   b-&gt;h4 i1-&gt;h4 i2-&gt;h4 i3-&gt;h4 
    0.16  -0.46   2.09   0.23 
  
  Weights for node h5:
   b-&gt;h5 i1-&gt;h5 i2-&gt;h5 i3-&gt;h5 
   -0.16  -0.55  -0.52   0.25 
  
  Weights for node h6:
   b-&gt;h6 i1-&gt;h6 i2-&gt;h6 i3-&gt;h6 
   -1.49  -7.07   1.67  -0.21 
  
  Weights for node h7:
   b-&gt;h7 i1-&gt;h7 i2-&gt;h7 i3-&gt;h7 
    2.00   1.67  -5.51   0.66 
  
  Weights for node h8:
   b-&gt;h8 i1-&gt;h8 i2-&gt;h8 i3-&gt;h8 
    0.56   0.44   0.41   0.51 
  
  Weights for node h9:
   b-&gt;h9 i1-&gt;h9 i2-&gt;h9 i3-&gt;h9 
    0.38   0.21   0.47  -0.41 
  
  Weights for node h10:
   b-&gt;h10 i1-&gt;h10 i2-&gt;h10 i3-&gt;h10 
     0.53   -1.60    4.79   -0.04 
  
  Weights for node o:
    b-&gt;o  h1-&gt;o  h2-&gt;o  h3-&gt;o  h4-&gt;o  h5-&gt;o  h6-&gt;o  h7-&gt;o  h8-&gt;o  h9-&gt;o 
    1.08   1.83   0.17   1.21   1.21   0.64  -0.13  -8.37   0.98   2.03 
  h10-&gt;o  i1-&gt;o  i2-&gt;o  i3-&gt;o 
   -8.41   0.03   0.00   0.01 
  </code></pre>
  
  <p>Thank you very much</p>