Databricks Certified Machine Learning - Associate
Get started today
Ultimate access to all questions.
Comments
Loading comments...
Ultimate access to all questions.
What is the primary drawback of using one-hot encoding for high cardinality categorical variables in a machine learning model?
A
One-hot encoding always leads to underfitting.
B
It decreases the dimensionality of the dataset.
C
One-hot encoding has no impact on computational complexity.
D
It increases the dimensionality of the dataset, potentially causing increased computational complexity and issues with model performance, such as overfitting.