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When developing a recommendation system in Databricks using collaborative filtering with the Alternating Least Squares (ALS) algorithm, which of the following is the most crucial consideration for optimizing ALS performance?
A
Preprocess the data to handle missing values before applying ALS.
B
Tune the regularization parameter to control model complexity.
C
Increase the number of ALS iterations for better convergence.
D
Use a larger number of latent factors for improved model accuracy.
