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  1. SystemDS
  2. SYSTEMDS-986

Add mllearn and scala wrappers for random forest

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    Description

      See https://apache.github.io/incubator-systemml/algorithms-classification.html#random-forests for usage.

      Since this is a starter task, I describe the steps to complete this task:
      1. Implement a scala class (which inherits from BaseSystemMLClassifier) similar to https://github.com/apache/incubator-systemml/blob/master/src/main/scala/org/apache/sysml/api/ml/NaiveBayes.scala
      2. Modify getTrainingScript and getPredictionScript to specify the parameters used. See the algorithm documentation for these parameters.
      3. Ensure that you implement appropriate traits to accept hyperparameters (eg: HasLaplace, HasIcpt, HasRegParam, HasTol, etc). These traits are available at https://github.com/apache/incubator-systemml/blob/master/src/main/scala/org/apache/sysml/api/ml/BaseSystemMLClassifier.scala#L36
      4. Implement a python class (that extends BaseSystemMLClassifier) with constructor similar to https://github.com/apache/incubator-systemml/blob/master/src/main/python/systemml/mllearn/estimators.py#L284 which essentially accepts the hyperparameters and invokes the scala side methods (example: self.estimator.setLaplace(laplace))
      5. Update the algorithm documentation by specifying the usage as well as examples.

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            sandeepn Sandeep Narayanaswami
            niketanpansare Niketan Pansare
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