You can tune any free parameters by defining a loss function. For example, you loss function can panelize two close points to be separated in two clusters and vice versa. Once you define loss function, it's just matter of finding optimal value - although at extra cost.
Comments
You can tune any free parameters by defining a loss function. For example, you loss function can panelize two close points to be separated in two clusters and vice versa. Once you define loss function, it's just matter of finding optimal value - although at extra cost.
One recently invested method of clustering called QuickCluster doesn't require any parameters and inherently operates on loss function. It's pretty fast in practice: http://www.cs.yale.edu/homes/el327/papers/CorrelationCluster...