When translating a decision tree from sklearn to Spark ML, an error occurs stating that the `maxBins` parameter should be at least equal to the number of values in each categorical feature. Why does Spark ML have this requirement? Choose only ONE best answer.

Real Exam

Spark ML tests only numeric features in the splitting algorithm

0.0%

Spark ML requires more split candidates in the splitting algorithm than single-node implementations

20.0%

Spark ML requires at least one bin for each category in each categorical feature

76.0%

Spark ML tests only categorical features in the splitting algorithm

4.0%

Databricks Certified Machine Learning - Associate