0

I am using pyspark through Jupyterlab to build decision tree using following code:

from pyspark.ml.classification import DecisionTreeClassifier
# train our model using training data
dt = DecisionTreeClassifier(labelCol="labelIndex", featuresCol="features")
model = dt.fit(training)

when i do print(model.toDebugString) then i get decision tree as :

DecisionTreeClassificationModel: uid=DecisionTreeClassifier_b62e15bb102c, depth=5, numNodes=11, numClasses=2, numFeatures=6
  If (feature 3 <= 5.5)
   Predict: 0.0
  Else (feature 3 > 5.5)
   If (feature 1 <= 8.5)
    If (feature 5 <= 0.5)
     Predict: 0.0
    Else (feature 5 > 0.5)
     If (feature 3 <= 23.5)
      Predict: 0.0
     Else (feature 3 > 23.5)
      If (feature 5 <= 11.5)
       Predict: 1.0
      Else (feature 5 > 11.5)
       Predict: 0.0
   Else (feature 1 > 8.5)
    Predict: 0.0

But i want to Visualize this to rule set into decision tree diagram ? Anyone knows how to do that ?

Saurabh Deshpande
  • 25
  • 4
  • 1
    Does this answer your question? [How do I visualise / plot a decision tree in Apache Spark (PySpark 1.4.1)?](https://stackoverflow.com/questions/31853979/how-do-i-visualise-plot-a-decision-tree-in-apache-spark-pyspark-1-4-1) – Vlad Siv Nov 14 '21 at 12:34

0 Answers0