Explanation:
The primary drawback of one-hot encoding for high cardinality categorical variables is the significant increase in dataset dimensionality. This escalation can lead to heightened computational complexity and may adversely affect model performance, including risks of overfitting.
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What is a significant drawback of applying one-hot encoding to categorical variables with high cardinality?
A
It is not applicable for continuous numerical variables
B
It fails to scale numerical variables appropriately
C
It lacks the capability to process missing values in categorical variables
D
It does not contribute to identifying the optimal machine-learning algorithm
E
It escalates the dataset's dimensionality, potentially increasing computational complexity