title: Using NNET for classification
body: <p>I am new to neural networks and I have a question about classification with the nnet package.</p>
  
  <p>I have data which is a mixture of numeric and categoric variables. I wanted to make a win lose prediction by using nnet and a function call such as </p>
  
  <pre><code>nnet(WL~., data=training, size=10) 
  </code></pre>
  
  <p>but this gives a different result than if I use a dataframe  with only numeric versions of the variables (i.e. convert all the factors to numeric (except my prediction WL)). </p>
  
  <p>Can someone explain to me what is happening here? I guess nnet is interpreting the variables different but I would like to understand what is happening. I appreciate its difficult without any data to recreate the problem but I am just looking at a high level explanation of how neural networks are fitted using nnet. I cant find this anywhere.  Many thanks.</p>
  
  <pre><code>str(training)
  'data.frame':   1346 obs. of  9 variables:
   $ WL                   : Factor w/ 2 levels "win","lose": 2 2 1 1 NA 1 1 2 2 2 ...
   $ team.rank            : int  17 19 19 18 17 16 15 14 14 16 ...
   $ opponent.rank        : int  14 12 36 16 12 30 11 38 27 31 ...
   $ HA                   : Factor w/ 2 levels "A","H": 1 1 2 2 2 2 2 1 1 2 ...
   $ comp.stage           : Factor w/ 3 levels "final","KO","league": 3 3 3 3 3 3 3 3 3 3 ...
   $ days.since.last.match: num  132 9 5 7 14 7 7 7 14 7 ...
   $ days.to.next.match   : num  9 5 7 14 7 9 7 9 7 8 ...
   $ comp.last.match      : Factor w/ 5 levels "Anglo-Welsh Cup",..: 5 5 5 5 5 5 3 5 3 5 ...
   $ comp.next.match      : Factor w/ 4 levels "Anglo-Welsh Cup",..: 4 4 4 4 4 3 4 3 4 3 ...
  </code></pre>
  
  <p>vs</p>
  
  <pre><code>str(training.nnet)
  'data.frame':   1346 obs. of  9 variables:
   $ WL                   : Factor w/ 2 levels "win","lose": 2 2 1 1 NA 1 1 2 2 2 ...
   $ team.rank            : int  17 19 19 18 17 16 15 14 14 16 ...
   $ opponent.rank        : int  14 12 36 16 12 30 11 38 27 31 ...
   $ HA                   : num  1 1 2 2 2 2 2 1 1 2 ...
   $ comp.stage           : num  3 3 3 3 3 3 3 3 3 3 ...
   $ days.since.last.match: num  132 9 5 7 14 7 7 7 14 7 ...
   $ days.to.next.match   : num  9 5 7 14 7 9 7 9 7 8 ...
   $ comp.last.match      : num  5 5 5 5 5 5 3 5 3 5 ...
   $ comp.next.match      : num  4 4 4 4 4 3 4 3 4 3 ...
  </code></pre>