Cluster Validity

For supervised classification we have a variety of

measures to evaluate how good our model is

Accuracy, precision, recall

For cluster analysis, the analogous question is how to

evaluate the "goodness" of the resulting clusters?

But "clusters are in the eye of the beholder"!

In practice the clusters we find are defined by the clustering

algorithm

Then why do we want to evaluate them?

To avoid finding patterns in noise

To compare clustering algorithms

To compare two sets of clusters

To compare two clusters