BioArtlas clusters 81 bioart works using axis-aware representations and evaluates 800 combinations to find optimal Agglomerative clustering at k=15 on 4D UMAP, revealing four patterns in artist methods, techniques, time, and concepts.
Estimating the number of clusters in a data set via the gap statistic.Journal of the royal statistical society: series b (statistical methodology), 63(2):411–423
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BioArtlas: Computational Clustering of Multi-Dimensional Complexity in Bioart
BioArtlas clusters 81 bioart works using axis-aware representations and evaluates 800 combinations to find optimal Agglomerative clustering at k=15 on 4D UMAP, revealing four patterns in artist methods, techniques, time, and concepts.