title: R decision tree using all the variables
body: <p>I would like to perform a decision tree analysis. I want that the decision tree uses all the variables in the model. </p>
  
  <p>I also need to plot the decision tree. How can I do that in R?</p>
  
  <p>This is a sample of my dataset </p>
  
  <pre><code>&gt; head(d)
    TargetGroup2000 TargetGroup2012 SmokingGroup_Kai PA_Score wheeze3 asthma3 tres3
  1               2               2                4        2       0       0     0
  2               2               2                4        3       1       0     0
  3               2               2                5        1       0       0     0
  4               2               2                4        2       1       0     0
  5               2               3                3        1       0       0     0
  6               2               3                3        2       0       0     0
  &gt; 
  </code></pre>
  
  <p>I would like to use the formula </p>
  
  <pre><code>myFormula &lt;- wheeze3 ~ TargetGroup2000 + TargetGroup2012 + SmokingGroup_Kai + PA_Score
  </code></pre>
  
  <p>Note that all the variables are categorical.</p>
  
  <p>EDIT:
  My problem is that some variables do not appear in the final decision tree. 
  The deap of the tree should be defined by a penalty parameter  alpha. I do not know how to set this penalty in order that all the variables appear in my model.<br>
  In other words I would like a model that minimize the training error. </p>