Compute dispersion of a single cluster
compute_tightness(dists, cluster)A real number in \([0,1]\) representing the mean distance to the medoid of the cluster.
A distance matrix for points in the cluster.
A list containing named vectors, whose names are data point names and whose values are cluster labels
This method finds the medoid of the input data set and returns the average distance to the medoid, i.e., $$\tau(C) = \dfrac{1}{\left(|C|-1\right)}\displaystyle\sum_{i}\text{dist}(x_i, x_j)$$ where $$x_j = \text{arg}\,\min\limits_{x_j\in C}\, \sum_{x_i \in C, i\neq j}\text{dist}(x_i, x_j)$$ A smaller value indicates a tighter cluster based on this metric.