Databricks Certified Machine Learning - Associate
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Discuss the role of feature selection in AutoML. Explain how automated feature selection techniques can improve model performance and reduce computational costs. Provide examples of common feature selection methods used in AutoML.
A
Filter methods, wrapper methods, and embedded methods.
B
Correlation analysis, principal component analysis, and mutual information.
C
Recursive feature elimination, stepwise selection, and lasso regression.
D
Forward selection, backward elimination, and decision trees.