title: Understanding Spark RandomForest featureImportances results
body: <p>I'm using <code>RandomForest.featureImportances</code> but I don't understand the output result. </p>
  
  <p>I have 12 features, and this is the output I get. </p>
  
  <p>I get that this might not be an apache-spark specific question but I cannot find anywhere that explains the output.</p>
  
  <pre><code>// org.apache.spark.mllib.linalg.Vector = (12,[0,1,2,3,4,5,6,7,8,9,10,11],
   [0.1956128039688559,0.06863606797951556,0.11302128590305296,0.091986700351889,0.03430651625283274,0.05975817050022879,0.06929766152519388,0.052654922125615934,0.06437052114945474,0.1601713590349946,0.0324327322375338,0.057751258970832206])
  </code></pre>