Efficient algorithm to find the lowest value cluster in a series of values Let's say I have a list of numeric values that tend to be grouped into some number of clusters of values that are close to one another.
I'm aware of things like k-means to group these into groups of similar values, but I'm curious as to whether there's a faster and perhaps simpler algorithm to simply find all the values in the first or lowest valued cluster.
Example: take this sequence:
9,8,22,45,46,41,20,19,7,10,11,20,21,24

There are three clusters: one near about 10, one near 20, and one near 42. The algorithm in question might return:
8,9,7,10,11

These values are part of the lowest valued cluster of grouped values. Whether the results are sorted or not doesn't matter.
I can think of some easy improvised ways but I'm wondering if there's a robust general solution.
Sort your data. That is the fast trick that you cannot do on multivariate data. Then solid for r by three largest gaps or using KDE.

Clustering is more interesting for multivariate data.