ClustML: A measure of cluster pattern complexity in scatterplots learnt from human-labeled groupings

• Published in: Information visualization Vol. 23; no. 2; pp. 105 - 122
• Main Authors: Hamza, Mostafa M, Ullah, Ehsan, Baggag, Abdelkader, Bensmail, Halima, Sedlmair, Michael, Aupetit, Michael
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.04.2024; SAGE PUBLICATIONS, INC
• Subjects: Clusters; Complexity; Probabilistic models; Visualization; perceptual data; Visual quality measure; data-driven; cluster pattern; Gaussian mixture model

Visual quality measures (VQMs) are designed to support analysts by automatically detecting and quantifying patterns in visualizations. We propose a new VQM for visual grouping patterns in scatterplots, called ClustML, which is trained on previously collected human subject judgments. Our model encode...