Databricks Certified Machine Learning - Associate
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Describe the process of one-hot encoding categorical features. Explain why this method can be inefficient for tree-based models and suggest an alternative approach for handling categorical data in such models.
A
One-hot encoding creates binary variables for each category, which can lead to high dimensionality and sparse data.
B
One-hot encoding is efficient for all types of models, including tree-based models.
C
One-hot encoding should not be used for categorical data.
D
One-hot encoding is only suitable for linear models.