HI All,

I am using Spark 1.6 and Pyspark.

I am trying to build a Randomforest classifier model using mlpipeline and
in python.

When I am trying to print the model I get the below value.

RandomForestClassificationModel (uid=rfc_be9d4f681b92) with 10 trees

When I use MLLIB RandomForest model with toDebugString I get all the rules
used for building the model.


  Tree 0:
    If (feature 53 <= 0.0)
     If (feature 49 <= 0.0)
      If (feature 3 <= 1741.0)
       If (feature 47 <= 0.0)
        Predict: 0.0
       Else (feature 47 > 0.0)
        Predict: 0.0
      Else (feature 3 > 1741.0)
       If (feature 47 <= 0.0)
        Predict: 1.0
       Else (feature 47 > 0.0)

How can I achieve the same thing using MLpipelines model.

Thanks in Advance.

Vishnu

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