clusters
Data structs and algorithms for clustering data observations and basic computations in n-dimensional spaces.
Example
import "github.com/muesli/clusters"
// fake some observations
var o clusters.Observations
o = append(o, clusters.Coordinates{1, 1})
o = append(o, clusters.Coordinates{3, 2})
o = append(o, clusters.Coordinates{5, 3})
// seed a new set of clusters
c, err := clusters.New(2, o)
// add observations to clusters
c[0].Append(o[0])
c[1].Append(o[1])
c[1].Append(o[2])
// calculate the centroids for each cluster
c.Recenter()
// find the nearest cluster for an observation
i := c.Nearest(o[1])
// => returns index 1
// find the neighbouring cluster and its average distance for an observation
i, d := c.Neighbour(o[0], 0)
// => returns index 1 with euclidean distance 12.5Development
