Results 41 to 50 of about 559,125 (302)
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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Scalability of efficient parallel K-Means [PDF]
, 2009 Clustering is defined as the grouping of similar items in a set, and is an important process within the field of data mining. As the amount of data for various applications continues to increase, in terms of its size and dimensionality, it is necessary ...
Giuseppe Di Fatta +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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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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K-Means Algorithm to Identify the Elderly Psychological Stress Analysis Algorithm
Advances in Multimedia, 2022 In order to study the psychological anxiety of the elderly, a psychological stress recognition algorithm based on ECG signal acquisition and heart rate variability was proposed based on the K-means algorithm. By collecting ECG signals of the elderly, HRV
Yan Gao
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MACOC: a medoid-based ACO clustering algorithm [PDF]
, 2014 The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning
Otero, Fernando E. B. +7 more
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, 2012 Clustering text documents is a fundamental task in modern data analysis, requiring approaches which perform well both in terms of solution quality and computational efficiency.
Kurt Hornik +7 more
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Image segmentation based on adaptive K-means algorithm
EURASIP Journal on Image and Video Processing, 2018 Image segmentation is an important preprocessing operation in image recognition and computer vision. This paper proposes an adaptive K-means image segmentation method, which generates accurate segmentation results with simple operation and avoids the ...
Xin Zheng +4 more
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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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Clustering dichotomously scored items through functional k-means algorithm
, 2016 In the educational field, it is common to analyze the probability of a correct response to a test item as a continuous function of the item parameters and the subject ability. This relation is given by the item response function.
Di Battista, Tonio; Dipartimento di Metodi Quantitativi e Teoria Economica, Università "G. d'Annunzio" Chieti-Pescara +1 more
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