Constructor for ClusterHierarchical.
double symmetric matrix containing the distance (or similarity) matrix. int identifying the clustering method to use. int identifying the type of transformation applied to the measures in dist. On input, only the upper triangular part of dist needs to be present. ClusterHierarchical saves the upper triangular part in the lower triangle. On return, the upper triangular part of dist is restored, and the matrix is made symmetric.
| method | Description |
|---|---|
| 0 | Single linkage (minimum distance). |
| 1 | Complete linkage (maximum distance). |
| 2 | Average distance within (average distance between objects within he merged cluster). |
| 3 | Average distance between (average distance between objects in the two clusters). |
| 4 | Ward's method (minimize the within-cluster sums of squares). For Ward's method, the elements of dist are assumed to be Euclidean distances. |
| transform | Description |
|---|---|
| 0 | No transformation is required. The elements ofdist are distances. |
| 1 | Convert similarities to distances by multiplying -1.0. |
| 2 | Convert similarities (usually correlations) to distances by taking the reciprocal of the absolute value. |
ClusterHierarchical Class | Imsl.Stat Namespace