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In the context of enhancing model performance through feature selection in your machine learning project, which Databricks MLlib-supported technique is adept at identifying the most pertinent features from a vast dataset?
A
Feature Scaling
B
Recursive Feature Elimination
C
Principal Component Analysis
D
Feature Importance Ranking