Results 41 to 50 of about 30,970,765 (331)
CoRR, 2022 The $k$-means is one of the most important unsupervised learning techniques in statistics and computer science. The goal is to partition a data set into many clusters, such that observations within clusters are the most homogeneous and observations between clusters are the most heterogeneous.
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CoRR, 2023 Leibniz International Proceedings in Informatics (LIPIcs ...
Grunau, Christoph +2 more
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Unsupervised Multi-View K-Means Clustering Algorithm
IEEE Access, 2023 Since advanced technologies via social media, internet, virtual communities and networks and internet of things (IoT), there are more multi-view data to be collected.
Miin-Shen Yang, Ishtiaq Hussain
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, 2023 Variability of the used K-Means implementation for 1000 executions on the features provided by PCA using k-means++ initialization. (TIF)
Ana-Maria Ichim (14648702) +4 more
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K-means** - a fast and efficient K-means algorithms
International Journal of Intelligent Information and Database Systems, 2018 K-means often converges to a local optimum. In improved versions of K-means, k-means++ is well-known for achieving a rather optimum solution with its cluster initialisation strategy and high computational efficiency. Incremental K-means is recognised for its converging to the empirically global optimum but having a high complexity due to its stepping ...
Cuong Duc Nguyen, Trong Hai Duong
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Clustering models for hospitals in Jakarta using fuzzy c-means and k-means
Procedia Computer Science, 2023 After facing the COVID-19 pandemic, national and local governments in Indonesia realized a gap in the distribution of health care and human health practitioners.
Karli Eka Setiawan +3 more
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$k$-means clustering of extremes [PDF]
Electronic Journal of Statistics, 2020 The $k$-means clustering algorithm and its variant, the spherical $k$-means clustering, are among the most important and popular methods in unsupervised learning and pattern detection. In this paper, we explore how the spherical $k$-means algorithm can be applied in the analysis of only the extremal observations from a data set.
Janßen, Anja, Wan, Phyllis
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Bulletin of the History of Archaeology, 2015 New Deal archaeology survey and excavation projects across the lower 48 states exhibit considerable geographic variation in their nature and extent. Part of this variation can be linked to strong regional personalities, while other variation depended on ...
Bernard K. Means
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Improved YOLOv5m model based on Swin Transformer, K-means++, and Efficient Intersection over Union (EIoU) loss function for cocoa tree (Theobroma cacao) disease detection [PDF]
Journal of Plant Protection ResearchThe cocoa tree is prone to diverse diseases such as stem borer, stem canker, swollen shot, and root rot disease which impedes high yield. Early disease detection is a critical component of diverse management processes that are implemented throughout the ...
Benedicta Nana Esi Nyarko +3 more
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