4. METHOD OF SOLUTION
Any normalization is done first. Three types of normalization are available - one is based entirely on the values of the input data, another based on scaled values resulting from user-defined weighting, and a third based on class stratific- ation. Next distances between objects are determined according to the metric chosen. Ten choices of metric are provided including Euclidean, Pearson and Spearman correlation, and the Tukey-Fisher distance metric. Then, agglomerative hierarchical cluster analysis is performed according to the clustering criterion selected, which may be single linkage, complete linkage, group or weighted average, centroid, median, Ward's method, or variance.