CciMST: A Clustering Algorithm Based on Minimum Spanning Tree and Cluster Centers

Algorithm 3

Pseudocode of Intracluster compactness.

) Input: Data set , the total number of points n, the number of clusters K,

the clustering result , K-1 inconsistent edges , the

geodesic distance between points x_i and x_j

) Output: Intracluster compactness CP

) Begin

Sort the pairwise geodesic distances of all points from

Extract the top 20% maximum geodesic distance (here, suppose there are a total of

maximum geodesic distances)

Calculate the average of the maximum geodesic distances

Calculate the intracluster distance for the ,

Calculate

Calculate the intracluster compactness of data set X, ( is the weight of Cluster_i)

) End