01 · Understand the idea
In simple words
Clustering groups similar examples without requiring a label for every group beforehand. Imagine sorting unknown buttons by shape and size. Another person might sort the same buttons by colour and material. The groups depend on the features and similarity rules you choose, so there may not be one correct answer.
Two useful terms
Cluster: a group formed by the method. Distance: a measure of how different two examples are.
Build your understanding
Clustering groups examples according to a similarity definition. It does not discover objectively correct categories automatically. The chosen features, scaling and distance strongly affect the groups. Use clustering to explore patterns, then inspect whether they support a useful interpretation.
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