Results 31 to 40 of about 1,986,530 (277)
Review of K-means Algorithm Optimization Based on Differential Privacy [PDF]
Jisuanji kexue, 2022 Differential privacy K-means algorithm (DP K-means),as a kind of privacy preserving data mining (PPDM) model based on differential privacy technology,has attracted much attention from researchers because of its simplicity,efficiency and ability to ...
KONG Yu-ting, TAN Fu-xiang, ZHAO Xin, ZHANG Zheng-hang, BAI Lu, QIAN Yu-rong
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Soil data clustering by using K-means and fuzzy K-means algorithm
Telfor Journal, 2016 A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering.
E. Hot, V. Popović-Bugarin
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Parallel Implementation of K-Means Algorithm on FPGA
IEEE Access, 2020 The K-means algorithm is widely used to find correlations between data in different application domains. However, given the massive amount of data stored, known as Big Data, the need for high-speed processing to analyze data has become even more critical,
Leonardo A. Dias +2 more
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An efficient $k$-means-type algorithm for clustering datasets with incomplete records [PDF]
, 2018 The $k$-means algorithm is arguably the most popular nonparametric clustering method but cannot generally be applied to datasets with incomplete records.
Lithio, Andrew, Maitra, Ranjan
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Patient Data Analysis with the Quantum Clustering Method
Quantum Reports, 2023 Quantum computing is one of the most promising solutions for solving optimization problems in the healthcare world. Quantum computing development aims to light up the execution of a vast and complex set of algorithmic instructions. For its implementation,
Shradha Deshmukh +2 more
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Fast Color Quantization Using Weighted Sort-Means Clustering [PDF]
, 2009 Color quantization is an important operation with numerous applications in graphics and image processing. Most quantization methods are essentially based on data clustering algorithms.
Balasubramanian +34 more
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Accelerated K-means Clustering Algorithm [PDF]
International Journal of Information Technology and Computer Science, 2016 Optimizing K-means is still an active area of research for purpose of clustering. Recent developments in Cloud Co mputing have resulted in emergence of Big Data Analytics. There is a fresh need of simp le, fast yet accurate algorithm for clustering huge amount of data.
Preeti Jain, Bala Buksh
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Jurnal Saintekom, 2023 K-Means algorithm as a method of grouping a set of data. The purpose of this study is to find out the use of the K-Means algorithm for outgoing mail data. The method used in this study focuses on the K-Means method. The grouping data used is 284 outgoing
Lili Rusdiana, Veny Cahya Hardita
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A bi-criteria approximation algorithm for $k$ Means [PDF]
, 2015 We consider the classical $k$-means clustering problem in the setting bi-criteria approximation, in which an algoithm is allowed to output $\beta k > k$ clusters, and must produce a clustering with cost at most $\alpha$ times the to the cost of the ...
Makarychev, Konstantin +3 more
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A Faster $k$-means++ Algorithm
, 2022 $k$-means++ is an important algorithm for choosing initial cluster centers for the $k$-means clustering algorithm. In this work, we present a new algorithm that can solve the $k$-means++ problem with nearly optimal running time. Given $n$ data points in $\mathbb{R}^d$, the current state-of-the-art algorithm runs in $\widetilde{O}(k )$ iterations, and ...
Liang, Jiehao +5 more
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