title: Pyspark: K means result with distance or deviation?
body: <p>From <a href="https://spark.apache.org/docs/2.2.0/ml-clustering.html#k-means" rel="noreferrer">https://spark.apache.org/docs/2.2.0/ml-clustering.html#k-means</a></p>
  
  <p>I know that after <code>kmModel.transform(df)</code>, there is a <code>prediction</code> column of the output dataframe stating which column a record/point belongs to.</p>
  
  <p>However, I'd also like tho know how each record/point deviate from the centroid, so I know what points in this cluster are typical, and what may stand between clusters</p>
  
  <p>How can I do it? It seems not implemented by the package by default</p>
  
  <p>Thanks!</p>