The Core Cluster-Based Subspace Weighted Clustering Ensemble
Algorithm 1
Input: ,
Output:
1. Performed clustering on each base subspace to generate a set of subspace clustering ensemble
2. Generate the adaptive core clusters according to Definition 1
3. Calculates the average distance between core clusters according to Equations (8) and (9)
4. Calculates the CSI of the cluster according to Equation (10), and is achieved according to Equation (11)–(13)
5. Construct the core cluster similarity matrix () according to Equations (14) and (15), and the weighted core cluster similarity matrix according to Equation (16).
6. Initialize
7. Construct the dendrogram
for to do
According to , merge the two most similar regions to achieve
Update , and achieve
end for
8. Select the level of the dendrogram according to , and achieve clusters
