title: Is there a way to call the 'predict' method of a Spark ML MultilayerPerceptronClassificationModel?
body: <p>For older ML models such as DecisionTreeModel it is possible to load a stored model and apply it directly to a single data point (feature vector) like this: </p>
  
  <pre><code>val features: Vector = &lt;some vector of floats representing feature values&gt; 
  val modelDT = DecisionTreeModel.load(sparkContext, &lt;"some-path"&gt;)
  val prediction = modelDT.predict(features)
  </code></pre>
  
  <p>For MultilayerPerceptronClassificationModel the predict method is protected and can't be called.  The features need to be wrapped in a Dataset, and the result is returned as a DataFrame with one row.  This is cumbersome and adds a lot of overhead for a real-time system that classifies one point at a time. </p>