Hierarchy of Groups Evaluation Using Different F-score Variants
This work addresses a rarely explored problem in clustering evaluation for researchers, but it appears incremental as it builds on existing F-score measures without claiming major breakthroughs.
The paper tackles the problem of evaluating hierarchical clustering quality by proposing three F-score variants (classic, hierarchical, and partial order), with the partial order index being the authors' novel approach. The experiments demonstrate the properties of these measures, highlighting their strengths and weaknesses.
The paper presents a cursory examination of clustering, focusing on a rarely explored field of hierarchy of clusters. Based on this, a short discussion of clustering quality measures is presented and the F-score measure is examined more deeply. As there are no attempts to assess the quality for hierarchies of clusters, three variants of the F-Score based index are presented: classic, hierarchical and partial order. The partial order index is the authors' approach to the subject. Conducted experiments show the properties of the considered measures. In conclusions, the strong and weak sides of each variant are presented.