title: Feeding large amounts of data into neuralnet function in R
body: <p>How would one feed say, 100 different cases into the <code>neuralnet()</code> function found in the <code>neuralnet</code> package without maunally inputting them.</p>
  
  <p>If there is a dataframe with <code>colnames(df) = "one","two","three"..."one hundred"</code></p>
  
  <p>and I want to use each column as an input into a neural network, is there a way to apply the <code>neuralnet</code> function as such:</p>
  
  <pre><code>nn &lt;- neuralnet(one~two+three+four+five+six+seven+eight...+one hundred, data=df, 
        err.fct = 'sse', linear.output = F, likelihood=T)
  </code></pre>
  
  <p>without actually typing all one hundred colnames.</p>
  
  <hr>
  
  <hr>
  
  <p>I have tried inputting:</p>
  
  <pre><code>nn &lt;- neuralnet(one~as.factor(paste(names(df)[-1], collapse="+")) data=df, 
        err.fct = 'sse', linear.output = F, likelihood=T)
  </code></pre>
  
  <p>and recieved the error</p>
  
  <pre><code>Error in model.frame.default(formula.reverse, data) : 
    variable lengths differ (found for 'as.factor(paste(names(df)[-1], collapse="+"))')
  </code></pre>