K-Means Clustering
4 centroids · 5 iterations · assign → mean → move centroid → recalculate distance → repeat
Pause
Restart
New run
speed
1×
1 · PICK SEEDS
2 · ASSIGN
3 · FIND MEAN
4 · RECALC DIST
5 · REPEAT
VECTOR SPACE
Iteration: 0 / 5
initializing
After each mean is found, the centroid moves to that mean. The next step explicitly draws distance arrows again before vectors are reassigned.