title: Decision tree completely different between rpart and party package
body: <p>I want to compare CART and CHAID algorithm, I choose rpart (cart algorithm) and party (chaid algorithm) to see the difference between them.
  My data is about blood pressure :
  <img src="https://i.stack.imgur.com/j47uK.png" alt="enter image description here"></p>
  
  <p>The party function returns me :</p>
  
  <pre><code>library(party)
  # par &lt;- ctree_control(minsplit=20, minbucket=10)
  arbre &lt;- ctree(bpress_level ~ ., data = df)
  arbre
  plot(arbre)
  </code></pre>
  
  <p><img src="https://i.stack.imgur.com/R5ka4.png" alt="enter image description here"></p>
  
  <p>The rpart package returns me :</p>
  
  <pre><code>library(rpart)
  fit &lt;- rpart(bpress_level ~ .,
               method="class", data=df)
  
  printcp(fit) # display the results
  plotcp(fit)
  
  plot(fit, uniform=TRUE,
       main="Classification Tree for pressure level")
  text(fit, use.n=TRUE, all=TRUE, cex=.8)
  </code></pre>
  
  <p><img src="https://i.stack.imgur.com/rEFkn.png" alt="enter image description here"></p>
  
  <p>I don't inderstand why the tree decisin are so different, is it normal ?
  Why for party package the algorithm ignores like smoke, stress, gender ....
  Thank you in advance. </p>