Model Training & Adaptation
Multiclass classification
Choosing one group from more than two possible groups.
Example
An AI system assigns a support message to billing, delivery or technical help.
Why people use it
It sorts cases when there are several possible categories but one is required.
What you'll hear
“Choose the best department for each request.”
What this means for you
Decide whether real cases need one category or multiple simultaneous labels.
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
- How is multiclass different from multilabel classification?
- Multiclass commonly chooses one group; multilabel allows several labels for one example.
- Can one common category dominate the results?
- Yes. A high overall score can hide poor performance on less common categories.
- What if the right category is missing from the list?
- The system may force a poor match unless an unknown or other option is available.