This approach is more likely to lead to a bad clustering result than the approach used by the demo. At the other extreme, a variation called k-means++ uses a moderately complex probabilistic algorithm ...

The clustering process starts with a copy of the first m items from the dataset. The initial clustering is [0, 1, . . m-1] so the first items are assigned to different clusters. This means that it's ...