March 28, 2024, 4:42 a.m. | Kento Urano, Ryo Yuki, Kenji Yamanishi

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.18269v1 Announce Type: cross
Abstract: This paper proposes an early detection method for cluster structural changes. Cluster structure refers to discrete structural characteristics, such as the number of clusters, when data are represented using finite mixture models, such as Gaussian mixture models. We focused on scenarios in which the cluster structure gradually changed over time. For finite mixture models, the concept of mixture complexity (MC) measures the continuous cluster size by considering the cluster proportion bias and overlap between clusters. …

abstract arxiv change cluster clustering complexity cs.it cs.lg data detection math.it paper stat.ml type

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