Classification
Definition
Classification assigns inputs to one or more discrete classes.
Models learn decision boundaries or probabilities for categories from labeled examples. Variants range from binary to multiclass to multilabel classification.
Simply explained
How to automatically sort incoming cases into predefined folders.
Why it matters in practice
Relevant for routing, quality control, documents, support, and many automations.
Example from business
A system classifies emails into invoice, complaint, delivery status, and others.
Limits and pitfalls
- Poorly define classes; ignore uncertainty; leak test data into training; use accuracy without error analysis.
Origin & history
Classification is a core problem of statistical learning and machine learning.
Use in mid-sized companies
- Possible application in SMEs: Use clearly defined classes, representative examples, and suitable error metrics.
Frequently asked questions
Is classification the same as clustering?
No, classification uses predefined labels; clustering searches for groups without such target classes.
Sources
- Classification · Google Machine Learning Glossary, Classification
Sources checked on 10.10.2026.
Editorially reviewed on: