Exam Certified Machine Learning Associate topic 1 question 33 discussion

A machine learning engineer is converting a decision tree from sklearn to Spark ML. They notice that they are receiving different results despite all of their data and manually specified hyperparameter values being identical. Which of the following describes a reason that the single-node sklearn decision tree and the Spark ML decision tree can differ? A. Spark ML decision trees test every feature variable in the splitting algorithm B. Spark ML decision trees automatically prune overfit trees C. Spark ML decision trees test more split candidates in the splitting algorithm D. Spark ML decision trees test a random sample of feature variables in the splitting algorithm E. Spark ML decision trees test binned features values as representative split candidates