| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 507575 | Computers & Geosciences | 2009 | 9 Pages |
Cluster analysis is used in numerous scientific disciplines. A method of cluster analysis based on graph theory is discussed and a MATLAB™ code for its implementation is presented. The algorithm is based on the number of variables that are similar between samples. By changing the similarity criterion in a stepwise fashion, a hierarchical group structure develops, and can be displayed by a dendrogram. Three indexes describe the homogeneity of a given variable in a group, the heterogeneity of that variable between two groups, and the usefulness of that variable in distinguishing two groups. The algorithm is applied to both a synthetic dataset and a set of trace element analyses of lavas from Mount Etna in order to compare GraphClus to other cluster analysis algorithms.
