LearnMachine learning
k-means clustering
Find groups in data that nobody has labelled, two simple steps at a time.
Click the chart to place the starting centres, then press Step or Run.
How it works
Groups without labels.
k-means is unsupervised: nobody tells it the right answer. You choose how many groups you want (k), and it finds k centres.
It repeats two simple steps. Assign: every point joins its nearest centre. Update: every centre moves to the middle of its points. When an assign step changes nothing, it has converged.
The result depends on where the centres start, so it can settle in a poor answer. In practice it is run several times from different starts, and the result with the smallest spread is kept.