Categorical Encoding vs Ordinal Encoding

Developers should learn categorical encoding when working with machine learning models, as most algorithms (e meets developers should use ordinal encoding when working with categorical features that have a clear ranking, such as education levels (e. Here's our take.

Categorical Encoding

Nice Pick

Developers should learn categorical encoding when working with machine learning models, as most algorithms (e

Pros

• g
• Related to: data-preprocessing, feature-engineering

Cons

• Specific tradeoffs depend on your use case

Ordinal Encoding

Developers should use ordinal encoding when working with categorical features that have a clear ranking, such as education levels (e

Pros

• g
• Related to: categorical-encoding, feature-engineering

Cons

• Specific tradeoffs depend on your use case

The Verdict

Use Categorical Encoding if: You want g and can live with specific tradeoffs depend on your use case.

Use Ordinal Encoding if: You prioritize g over what Categorical Encoding offers.

The Bottom Line

Categorical Encoding wins

Developers should learn categorical encoding when working with machine learning models, as most algorithms (e