Skip to content

Model Training & Adaptation

One-hot encoding

Representing categories with separate yes-or-no markers, usually written as ones and zeros.

Example

A color field becomes separate indicators for red, blue and green.

Why people use it

It lets software represent categories without pretending that one is numerically larger than another.

What you'll hear

“Give each color its own yes-or-no marker.”

What this means for you

Plan how unseen categories and large category lists will be handled.

Can you control it?

Developer-only

The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.

Common questions

Does one-hot encoding imply an order between categories?
No. It is designed to avoid an unintended numerical ordering.
Can it create a very wide table?
Yes. Each possible category needs its own place, so many categories can require substantial space.
What happens with a previously unseen category?
The system needs an agreed handling rule because the original set has no marker for it.

Related terms

Still have questions?

Up to 500 characters.

Ask LATHIC about AI. Relevant glossary entries may be included.

Your question, the glossary entries it matches, and a rotating pseudonymous identifier go to Microsoft Azure’s OpenAI service through Vercel AI Gateway to generate an answer. Zero retention and no training are required of the provider, and LATHIC does not save your question or answer. Privacy Notice