Clustering
Grouping similar items together without predefined categories, discovering natural clusters based on shared characteristics.
Plain English Explanation
Clustering groups similar items together without predefined categories. The system discovers natural clusters in data based on shared characteristics.
It is a core technique in unsupervised machine learning.
Analogy
Clustering is like organising a mixed box of photographs into piles of similar scenes — beaches, birthdays, landscapes — without anyone telling you the categories in advance.
How is it used?
Marketing teams segment customers by behaviour. News apps group related articles. Gene research groups similar DNA sequences.
Real-world Example
A retailer clusters shoppers into behaviour groups to tailor campaigns without manually defining segments upfront.
Common Misconceptions
Clusters are not always meaningful — algorithms will group data even when no natural structure exists.