There are related questions but the answers don't seem to explain how to practically judge these measurements for non stats users. I have a dataset which I clustered with K=4 using hierarchical clustering (complete and average methods) and kmeans, and have calculated VI, Rand, and Dunn indexes. I know this is very simplistic but from what I understand: for these measures higher is better (clusters are farther apart). But these metrics give me contrasting answers.
Methods HC-comp HC-avg K-means IV 1.6137 1.5365 1.5225 Rand 0.2703 0.2667 0.3914 Dunn 0.08468 0.07358 0.08006
Judging from these numbers: HC-comp is better according to IV and Dunn, but according to Rand K-means seem a better choice. Should I user other cluster statistics like average silhouette width, separation, diameter,etc?