FowlkesMallowsIndex computes the Fowlkes and Mallows index.

Fowlkes-Mallows index (see references) is an external evaluation method that is used to determine the similarity between two clusterings (clusters obtained after a clustering algorithm). This measure of similarity could be either between two hierarchical clusterings or a clustering and a benchmark classification. A higher the value for the Fowlkes-Mallows index indicates a greater similarity between the clusters and the benchmark classifications.

This index can be used to compare either two cluster label sets or a cluster label set with a true label set. The formula of the adjusted Fowlkes-Mallows index (ABk) is given below

\[ ABk= \frac{\mbox{Bk- Expected value of Bk}}{\mbox{Max Index - Expected value of Bk}} \]```
```

FM index (adjusted) with the contingency table as input.`ABk`

=FowlkesMallowsIndex(`c1`

,
`c2`

,
` noisecluster`

)

```
[
```

Compare FM (unadjusted) for iris data (true classification against tclust classification).`ABk`

,
`Bk`

]
=FowlkesMallowsIndex(___)

Fowlkes, E.B. and Mallows, C.L. (1983), A Method for Comparing Two Hierarchical Clusterings, "Journal of the American Statistical Association", Vol. 78, pp. 553-569.