Saferview - crime, fear, and mapping: Explaining clustering to non ...

In the previous posts on this topic I have given details of my dataset of 28 variables of police force expenditure, discussed how this can be mapped in 28 dimensional space to provide unique locations for each force, and then introduced the concept of dividing the forces into hierarchical clusters based on the locations of the forces. The process I illustrated was in the previous post was the divisive or top down approach that starts off with all the forces in one cluster and then divides into two, then three, then four clusters, etc. This starts with 43 separate clusters and ends up with one through the merging of clusters. The centroid of each cluster is therefore the location of that force in the 28 dimensional space that the computer calculates by plotting the values of the 28 variables relating to each force. It then merges the two clusters together (now there are 42 clusters) and calculates the centroid of that new cluster. I listed the forces in alphabetical order so the numbers relating to the clusters relate to the forces as shown (but remember by cluster 2 by stage 3 has two forces in it 2 & The stages refer to the stage in the process, so stage 1 is when 42 clusters are formed from 43.