# Q1d · Binary, multiclass and multilabel

Subject: Natural Language Processing

Exam: TEE

Reader: https://deep-learning-study-room.vercel.app/nlp/#tee/papers/legacy-f23/q1d

Canonical: https://deep-learning-study-room.vercel.app/read/nlp/tee/papers/legacy-f23--q1d/

Previous examination · complete worked answers

**Question. Compare binary, multiclass and multilabel supervised text classification with examples.** [5 marks]

### Answer

| Type | Allowed output | Example | Typical output rule |
| --- | --- | --- | --- |
| Binary | One of two labels | positive OR negative review | One sigmoid or two-class softmax |
| Multiclass | Exactly one of several labels | sport OR business OR science | Softmax over mutually exclusive classes |
| Multilabel | Zero, one or several labels | Article tagged technology AND finance | Independent sigmoid per label |

Multiclass and multilabel differ in whether labels may coexist, not merely in the number of labels. A loss and evaluation measure must match the task.