title: How Do I Turn My Decision Tree Classifier Into A Manual Process?
body: <p>I am attempting to create a normalization (classification) for certain rock types using scikit-learn. I have my classifier (using the sklearn.tree.DecisionTreeClassifier) and am attempting to turn it into some process that you could do implement paper if need be. The classifier uses 11 dimensional data like the following:        </p>
  
  <pre><code>ROCK NAME |SIO2 |TIO2| AL2O3|   CR2O3|  FEOT|   CAO|    MGO|    MNO|    K2O|    NA2O|   P2O5|  
  WEHRLITE    |45.42| 0.17|   2.57|   0.32|   11.3384|    7.54|   31.93|  0.17|   0.01|   0.24|   0.01|    
  </code></pre>
  
  <p>I already used tree.export_graphviz to develop a flowchart:
  <img src="https://i.stack.imgur.com/aq5yE.jpg" alt="enter image description here"></p>
  
  <p>This is how another type of normalization is laid out which I would like mine to be like:
  <a href="http://minerva.union.edu/hollochk/c_petrology/norms.htm" rel="nofollow noreferrer">link</a><br>
  any ideas?</p>