Farthest-first traversal

Farthest-first traversal is a strategy used primarily in clustering and data sampling algorithms. It is designed to efficiently explore data points in a dataset by selecting points that are as far away from existing selected points as possible. This approach is often used in scenarios where you want to create a representative sample of data or construct clusters that are well-distributed across the data space.