Basic working principle
Given N objects to be clustered and an N*N distance matrix (or similarity matrix), the basic steps of the hierarchical clustering method (see SC Johnson in 1967) are as follows:
1. Classified into one class, a total of N classes are obtained, and each class contains only one object. The distance between classes is the distance between the objects they contain.
2. Find the two closest classes and merge them into one, so the total number of classes is one less.
3. Recalculate the distance between the new class and all the old classes.
4. Repeat steps 2 and 3, Until finally merged into a class (this class contains N objects).