title: How to solve "The data cannot have more levels than the reference" error when using confusioMatrix?
body: <p>I'm using R programming.
  I divided the data as train &amp; test for predicting accuracy.</p>
  
  <p>This is my code:</p>
  
  <pre><code>library("tree")
  credit&lt;-read.csv("C:/Users/Administrator/Desktop/german_credit (2).csv")
  
  library("caret")
  set.seed(1000)
  
  intrain&lt;-createDataPartition(y=credit$Creditability,p=0.7,list=FALSE)
  train&lt;-credit[intrain, ]
  test&lt;-credit[-intrain, ]
  
  treemod&lt;-tree(Creditability~. , data=train)
  plot(treemod)
  text(treemod)
  
  cv.trees&lt;-cv.tree(treemod,FUN=prune.tree)
  plot(cv.trees)
  
  prune.trees&lt;-prune.tree(treemod,best=3)
  plot(prune.trees)
  text(prune.trees,pretty=0)
  
  install.packages("e1071")
  library("e1071")
  treepred&lt;-predict(prune.trees, newdata=test)
  
  confusionMatrix(treepred, test$Creditability)
  </code></pre>
  
  <p>The following error message happens in <code>confusionMatrix</code>:</p>
  
  <blockquote>
    <p>Error in confusionMatrix.default(rpartpred, test$Creditability) : the data cannot have more levels than the reference</p>
  </blockquote>
  
  <p>The credit data can download at this site.<br>
  <a href="http://freakonometrics.free.fr/german_credit.csv" rel="nofollow">http://freakonometrics.free.fr/german_credit.csv</a></p>