title: Neuralnet library in R gives different output every time
body: <p>I am trying to run a neural network in R using the neuralnet library and every time I run it, it gives me different results. Often it says 'the algorithm did not converge'. I have tried varying the amount of hidden layers, the threshold, the repetitions and nothing seems to work. My dataset is about 1100 rows, across 41 columns, and I am trying to use 40 of the columns to predict the 41st. Does anyone have any advice? Here is the code for the implementation I am currently using:-</p>
  
  <pre><code>n &lt;- names(train1)
  f &lt;- as.formula(paste("RESULT ~", paste(n[!n %in% "RESULT"], collapse = " + "))) 
  nn &lt;- neuralnet(f, data=train1, hidden=4,linear.output=FALSE, threshold = 0.1, rep=3)
  </code></pre>
  
  <p>Whereby train1 is my data set. Any help would be greatly appreciated!</p>