DATABRICKS-MACHINE-LEARNING-ASSOCIATE practice

Q1 Single choice

A data scientist wants to parallelize the training of trees in a gradient boosted tree to speed up the training process. A colleague suggests that parallelizing a boosted tree algorithm can be difficult.

Which of the following describes why?

A
Gradient boosting is not a linear algebra-based algorithm which is required for parallelization
B
Gradient boosting requires access to all data at once which cannot happen during parallelization.
C
Gradient boosting calculates gradients in evaluation metrics using all cores which prevents parallelization.
D
Gradient boosting is an iterative algorithm that requires information from the previous iteration to perform the next step.