title: Spark load model and continue training
body: <p>I'm using <strong>Scala</strong> with <strong>Spark 2.0</strong> to train a model with <strong>LinearRegression</strong>.</p>
  
  <pre><code>val lr = new LinearRegression()
    .setMaxIter(num_iter)
    .setRegParam(reg)
    .setStandardization(true)
  
  val model = lr.fit(data)
  </code></pre>
  
  <p>this is working fine and I get good results.
  I saved the model and loaded it in another class to make some predictions:</p>
  
  <pre><code>val model = LinearRegressionModel.load("models/LRModel")
  val result = model.transform(data).select("prediction")
  </code></pre>
  
  <p>Now I wanted to continue training the model with new data, so I saved the model and loaded it to continue the training.</p>
  
  <p>Saving:</p>
  
  <pre><code>model.save("models/LRModel")
  lr.save("models/LR")
  </code></pre>
  
  <p>Loading:</p>
  
  <pre><code>val lr = LinearRegression.load("models/LR")
  val model = LinearRegressionModel.load("models/LRModel")
  </code></pre>
  
  <p>The Problem is, when I load the model, there is not <code>fit</code> or <code>train</code> function to continue the training.
  When I load the LinearRegression object it seems like it does not save the weights, only the parameters for the algorithm.
  I tested it by training the same data for the same number of iterations and the result was the exact same <code>rootMeanSquaredError</code> and it was definitely not converged at this point of learning.
  I also can not load the model into the LinearRegression, it results in a error:</p>
  
  <pre><code>Exception in thread "main" java.lang.NoSuchMethodException: org.apache.spark.ml.regression.LinearRegressionModel.&lt;init&gt;(java.lang.String)
  </code></pre>
  
  <p>So the question is, how do I get the LinearRegression object to use the saved LinearRegressionModel?</p>