Results 21 to 30 of about 18,390,026 (306)
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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Towards optimal lower bounds for k-median and k-means coresets [PDF]
Symposium on the Theory of Computing, 2022 The (k,z)-clustering problem consists of finding a set of k points called centers, such that the sum of distances raised to the power of z of every data point to its closest center is minimized.
Vincent Cohen-Addad +3 more
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The development of a GIS for New Deal Archaeology
Bulletin of the History of Archaeology, 2011 I have recently launched an effort to create a GIS of all New Deal-funded archaeological investigations conducted in the 48 states that comprised the USA during the Great Depression (Means 2011).
Bernard K. Means
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Optimized K‐Means Algorithm [PDF]
Mathematical Problems in Engineering, 2014 The localization of the region of interest (ROI), which contains the face, is the first step in any automatic recognition system, which is a special case of the face detection. However, face localization from input image is a challenging task due to possible variations in location, scale, pose, occlusion, illumination, facial expressions, and clutter ...
Samir Brahim Belhaouari +2 more
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B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM
Journal of Theoretical and Applied Electronic Commerce Research, 2022 Customer churn prediction is very important for e-commerce enterprises to formulate effective customer retention measures and implement successful marketing strategies.
Xiancheng Xiahou, Yoshio Harada
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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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K-means and fuzzy c-means algorithm comparison on regency/city grouping in Central Java Province
Desimal, 2022 The Human Development Index (HDI) is very important in measuring the country's success as an effort to build the quality of life of people in a region, including Indonesia. The government needs to make groupings based on the needs of a city/district.
Ummu Wachidatul Latifah +2 more
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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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Quantum Clustering with k-Means: a Hybrid Approach [PDF]
Theoretical Computer Science, 2022 Quantum computing is a promising paradigm based on quantum theory for performing fast computations. Quantum algorithms are expected to surpass their classical counterparts in terms of computational complexity for certain tasks, including machine learning.
Alessandro Poggiali +4 more
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The comparative study of text documents clustering algorithms
Environment Conservation Journal, 2015 Clustering is one of the most significant research area in the field of data mining and considered as an important tool in the fast developing information explosion era.Clustering systems are used more and more often in text mining, especially in ...
Mohammad Eiman Jamnezhad, Reza Fattahi
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