Computer Science
a year ago

New clustering algorithm boosts accuracy in data analysis by 2.6%!

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Engineering Applications of Artificial Intelligence
Semi-supervised hierarchical ensemble clustering based on an innovative distance metric and constraint information
Baohua Shen, Juan Jiang, Feng Qian, Daoguo Li, Yanming Ye, Gholamreza Ahmadi

Paper Summary

The article introduces a new clustering method called SSEHCCI, which combines different clustering algorithms to improve accuracy. This method uses class information and constraints to group objects together more effectively. By using a unique distance measure, SSEHCCI outperformed other semi-supervised algorithms on certain datasets, showing an average accuracy increase of 2.6% compared to SSDC and 1.8% compared to RSSC.

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