Results 21 to 30 of about 11,198,909 (310)
Kernel Probabilistic K-Means Clustering
Sensors, 2021 Kernel fuzzy c-means (KFCM) is a significantly improved version of fuzzy c-means (FCM) for processing linearly inseparable datasets. However, for fuzzification parameter m=1, the problem of KFCM (kernel fuzzy c-means) cannot be solved by Lagrangian ...
Bowen Liu +4 more
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Proceedings of the VLDB Endowment, 2012 Over half a century old and showing no signs of aging, k -means remains one of the most popular data processing algorithms. As is well-known, a proper initialization of k -means is crucial for obtaining a good final solution.
Bahman Bahmani +4 more
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CoRR, 2023 Leibniz International Proceedings in Informatics (LIPIcs ...
Grunau, Christoph +2 more
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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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Metode Boost-K-means untuk Clustering Puskesmas berdasarkan Persentase Bayi yang Diimunisasi
JRST: Jurnal Riset Sains dan Teknologi, 2020 Dinas Kesehatan Kabupaten/Kota adalah satuan kerja pemerintahan daerah kabupaten/kota yang bertanggung jawab menyelenggarakan urusan pemerintahan dalam bidang kesehatan di kabupaten/kota.
Ahmad Irfan Abdullah +2 more
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Customer analytics for online retailers using weighted k-means and RFM analysis
Data Analytics and Applied Mathematics, 2023 In recent years, there has been a significant trend toward data-driven enterprises in the business world. This trend is exemplified by the frustration reported by 74% of customers when they encounter ads that are not relevant to them, as reported by ...
Ahmed Mohamed Ahmed Serwah +3 more
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Optimized Cartesian K-Means [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2015 Product quantization-based approaches are effective to encode high-dimensional data points for approximate nearest neighbor search. The space is decomposed into a Cartesian product of low-dimensional subspaces, each of which generates a sub codebook. Data points are encoded as compact binary codes using these sub codebooks, and the distance between two
Jianfeng Wang +5 more
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The Monongahela tradition in "real time": Bayesian analysis of radiocarbon dates.
PLoS ONE, 2022 Despite advances in techniques, methods, and theory, northeastern North American archaeologists continue to use early to mid-twentieth century culture historical taxa as units of analysis and narrative.
John P Hart, Bernard K Means
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Penggunaan Metode K-Means dan K-Means++ Sebagai Clustering Data Covid-19 di Pulau Jawa
Teknika, 2022 Virus Corona (Covid-19) merupakan penyakit menular yang dapat ditularkan antara hewan dan manusia. Pada akhir Desember 2019, virus itu teridentifikasi di Provinsi Wuhan, Cina.
Nursatio Nugroho, Faisal Dharma Adhinata
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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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