A Propound Method for the Improvement of Cluster Quality
This is an incremental improvement for clustering in the educational domain.
The paper tackles the problem of improving cluster quality by proposing the Knockout Refinement Algorithm (KRA) to refine clusters from SOM and K-Means, and results show it generates better quality clusters with improved metric values in the educational domain.
In this paper Knockout Refinement Algorithm (KRA) is proposed to refine original clusters obtained by applying SOM and K-Means clustering algorithms. KRA Algorithm is based on Contingency Table concepts. Metrics are computed for the Original and Refined Clusters. Quality of Original and Refined Clusters are compared in terms of metrics. The proposed algorithm (KRA) is tested in the educational domain and results show that it generates better quality clusters in terms of improved metric values.