Results 11 to 20 of about 559,125 (302)
Acta Informatica Pragensia, 2023 This paper presents two novel deterministic initialization procedures for k-means clustering based on a modified crowding distance. The procedures, named ck-means and fck-means, use more crowded points as initial centroids.
Abdesslem Layeb
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Genetic K-means algorithm [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 1999 In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partition of a given data into a specified number of clusters. GA's used earlier in clustering employ either an expensive crossover operator to generate valid child chromosomes from parent chromosomes or a costly fitness function or both.
Krishna, K, Murty, Narasimha M
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A Faster $k$-means++ Algorithm
CoRR, 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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Interpretation and optimization of the k-means algorithm [PDF]
Applications of Mathematics, 2014 The paper gives a new interpretation and a possible optimization of the well known k-means algorithm for searching for a locally optimal partition of the set A={; ; _ ⋲Rn: =1, …, }; ; which consists of k disjoint non empty subsets 1, , .. , 1≤k≤m. For this purpose, a new divided k-means algorithm was constructed as a limit case of the known smoothed k ...
Sabo, Kristian, Scitovski, Rudolf
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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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An improved K‐means algorithm for big data
IET Software, 2022 An improved version of K‐means clustering algorithm that can be applied to big data through lower processing loads with acceptable precision rates is presented here.
Fatemeh Moodi, Hamid Saadatfar
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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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K-means Clustering, Unsupervised Classification, K-NN, Euclidean Distance, Genetic Algorithm
Tikrit Journal of Pure Science, 2023 In recent days, the need to provide reliable data transmission over Internet traffics or cellular mobile systems becomes very important. Transmission Control Protocol (TCP) represents the prevailing protocol that provide reliability to data transferring
Maaeda Mohsin Rashid
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An Incremental K-means algorithm [PDF]
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2004 Data clustering is an important data exploration technique with many applications in engineering, including parts family formation in group technology and segmentation in image processing. One of the most popular data clustering methods is K-means clustering because of its simplicity and computational efficiency.
Pham, Duc Truong +2 more
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Establish intelligent detection system to evaluate the sugar smoking of chicken thighs
Poultry Science, 2021 : The objective of this study was to establish a standardized color detection method to achieve low-cost, rapid, nonintrusive and accurate characterization of the color change of smoked chicken thighs during the smoking process.
Bo Wang +8 more
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