Different Aspects of Cluster Validation

Determining the clustering tendency of a set of data, i$.$e$.,$

distinguishing whether non$-$random structure actually exists in the

data.

Comparing the results of a cluster analysis to externally known

results, e$.$g$.,$ to externally given class labels.

Evaluating how well the results of a cluster analysis fit the data

without reference to external information.

Use only the data

Comparing the results of two different sets of clusters $($generated for

the same data$)$ to determine which is better.

Determining the 'correct' number of clusters.

For $2$ and $3,$ we can further distinguish whether we want to evaluate

the entire clustering or just individual clusters.