Results 41 to 50 of about 1,246,571 (292)
An Algorithm for Online K-Means Clustering [PDF]
2016 Proceedings of the Eighteenth Workshop on Algorithm Engineering and Experiments (ALENEX), 2015 This paper shows that one can be competitive with the k-means objective while operating online. In this model, the algorithm receives vectors v_1,...,v_n one by one in an arbitrary order. For each vector the algorithm outputs a cluster identifier before receiving the next one.
Edo Liberty +2 more
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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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On the Consistency of k -means++ algorithm [PDF]
Fundamenta Informaticae, 2020 We prove in this paper that the expected value of the objective function of the k-means++ algorithm for samples converges to population expected value. As k-means++, for samples, provides with constant factor approximation for k-means objectives, such an approximation can be achieved for the population with increase of the sample size.
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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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, 2020 Lithium-ion batteries with high energy density have been widely used in energy storages and electrical vehicles. After retiring, they usually contain 70%-80% of their primary capacity and can still be reused for secondary applications.
Zihao Zhou +8 more
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K+ Means : An Enhancement Over K-Means Clustering Algorithm
CoRR, 2017 Authors: Co-author's name added Section 3: Step (a) and (b) of K+Means algorithm are merged for simplicity. Section 3.1: K+ Means algorithm complexity rectified.
Srikanta Kolay +2 more
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A Cheap Feature Selection Approach for the K-Means Algorithm
IEEE Transactions on Neural Networks and Learning Systems, 2020 The increase in the number of features that need to be analyzed in a wide variety of areas, such as genome sequencing, computer vision, or sensor networks, represents a challenge for the $K$ -means algorithm.
Marco Capó, Aritz Pérez, J. A. Lozano
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Evaluation of modified adaptive k-means segmentation algorithm
Computational Visual Media, 2019 Segmentation is the act of partitioning an image into different regions by creating boundaries between regions. k-means image segmentation is the simplest prevalent approach.
Taye Girma Debelee +3 more
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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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Turbid of Water By Using Fuzzy C- Means and Hard K- Means
مجلة بغداد للعلوم, 2020 In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected from the ...
Rand Muhaned Fawzi, Iden Hassan Alkanani
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