title: Trying to understand isolation forest algorithm
body: <p>I am trying to use <a href="http://scikit-learn.org/stable/auto_examples/ensemble/plot_isolation_forest.html#sphx-glr-auto-examples-ensemble-plot-isolation-forest-py" rel="noreferrer">isolation forest algorithm</a> with Python scikit-learn. </p>
  
  <p>I do not understand why do I have to generate the sets <code>X_test</code> and <code>X_outliers</code>, because, when I get my data, I have no idea if there are outliers or not in it. But maybe this is just an example and I do not have to generate and fill that sets for every case. I thought that isolation forest does not have to receive a clean <code>X_train</code> (with no outliers).</p>
  
  <p>Did I misunderstand the algorithm? Do I have to use an other algorithm (I thought about one-class SVM but its <code>X_train</code> has to be as clean as possible)?</p>
  
  <p>Does the isolation forest algorithm is an unsupervised algorithm or a supervised one (like the random forest algorithm)?</p>