What is the primary consequence of applying One-Hot Encoding to a categorical feature with high cardinality?

Question

Data Science — Easy

What is the primary consequence of applying One-Hot Encoding to a categorical feature with high cardinality?

Accepted Answer

One-Hot Encoding creates a new binary column for every unique category in a feature. If a feature has high cardinality (many unique values), this process results in a sparse matrix with a very large number of columns, often referred to as the 'curse of dimensionality'. Option B describes Ordinal Encoding, not One-Hot Encoding.