Threshold Computation to Discover Cluster Structure: A New Approach
Year: 2016
Type: article
Abstract: Cluster members are decided based on how close they are with each other. Compactness of cluster plays an important role in forming better quality clusters. ICNBCF incremental clustering algorithm computes closeness factor between every two data series. To decide members of cluster, it is necessary to know one more decisive factor to compare, threshold. Internal evaluation measure of cluster like variance and dunn index provide required decisive factor. in intial phase of ICNBCF, this decisive factor was given manually by investigative formed closeness factors. With values generated by internal evaluation measure formule, this process can be automated. This paper shows the detailed study of various evaluation measuress to work with new incremental clustreing algorithm ICNBCF.
Author: Preeti Mulay
Institution: Symbiosis International University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2195830189