Clustering methods
Hierarchical clustering starts by calculating the distance between all possible combinations of two rows or columns using a selected distance measure. These calculated distances are then used to derive the distance between all clusters that are formed from the rows or columns during the clustering.
See also Distance measures.
You can select one of the following clustering methods:
- UPGMA
UPGMA stands for Unweighted Pair-Group Method with Arithmetic mean. - WPGMA
WPGMA stands for Weighted Pair-Group Method with Arithmetic mean. - Single linkage
This method is based on minimum distance. To calculate the distance between two clusters, each possible combination of two rows (or columns) between the two clusters is compared. The distance between the clusters is the same as the distance between the two rows (or columns) in the clusters that are least distant. - Complete linkage
This method is based on maximum distance and can be thought of as the opposite of Single linkage. To calculate the distance between two clusters, each possible combination of two rows (or columns) between the two clusters is compared. The distance between the two clusters is the same as the distance between the two rows (or columns) in the clusters that are most distant. - Ward's method
Ward's method means calculating the incremental sum of squares. Half square Euclidean distance is the only distance measure that can be used with this clustering method. Therefore, the distance measure is automatically set to Half square Euclidean distance when Ward's method is selected.
Parent topic: Hierarchical clustering