Manual Step by Step Single Link hierarchical clustering with dendrogram.

You are here because, you knew something about Hierarchical clustering and want to know how Single Link clustering works and how to draw a Dendrogram.

Hierarchical Clustering : Its slow :: complicated :: repeatable :: not suited for big data sets.

Lets take a 6 simple Vectors.

Using Euclidean Distance lets compute the Distance Matrix.
Euclidean Distance = sqrt( (x2 -x1)**2 + (y2-y1)**2 )

Example : Distance between A and B
sqrt ( (18- 22) ** 2 + (0–0) ** 2))
sqrt( (16) + 0)
sqrt(16)= 4

Single Link Clustering: Minimum of two distances. Leads to large more diverse clusters.

Distance Matrix: Diagonals will be 0 and values will be symmetric.

Step a: The shortest distance in the matrix is 1 and the vectors associated with that are C & D

So the first cluster is C — D

Distance between other vectors and CD

A to CD = min(A->C, A->D) = min(25,24) = 24
B to CD = min(B-<C, B->D) = min(21,20) = 20

and similarly find for E & F

Step b : Now 2 is the shortest distance and the vectors associated with that are E & F