title: In gbm multinomial dist, how to use predict to get categorical output?
body: <p>My response is a categorical variable (some alphabets), so I used distribution='multinomial' when making the model, and now I want to predict the response and obtain the output in terms of these alphabets, instead of matrix of probabilities.</p>
  
  <p>However in <code>predict(model, newdata, type='response')</code>, it gives probabilities, same as the result of <code>type='link'</code>.</p>
  
  <p>Is there a way to obtain categorical outputs?</p>
  
  <pre><code>BST = gbm(V1~.,data=training,distribution='multinomial',n.trees=2000,interaction.depth=4,cv.folds=5,shrinkage=0.005)
  
  predBST = predict(BST,newdata=test,type='response')
  </code></pre>