Results 61 to 70 of about 30,970,765 (331)
, 2021 The table of GECO scores generated after clustering with k-means using each value of k listed in the first column ‘k’. (CSV)
Akul Singhania (502117) +3 more
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Introduction to Geographic and Spatial Approaches in the History of Archaeology
Bulletin of the History of Archaeology, 2015 Who studies the historiography of archaeology? Who reads the history of the discipline? Recent years have seen growing interest in the history of archaeology as is reflected in works such as Christenson (1989), Trigger (1989; 2006), Chakrabarti (1988 ...
Neha Gupta, Bernard K Means
doaj +1 more source
Neurocomputing, 2018 Abstract Due to its simplicity and versatility, k-means remains popular since it was proposed three decades ago. The performance of k-means has been enhanced from different perspectives over the years. Unfortunately, a good trade-off between quality and efficiency is hardly reached. In this paper, a novel k-means variant is presented.
Wanlei Zhao +2 more
openaire +4 more sources
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
openaire +4 more sources
Advanced Approach of Material Region Detections on Fibre-Reinforced Concrete CT-Scans
Advances in Electrical and Electronic Engineering, 2017 Detections of material regions on CT-scans of solids are commonly treated manually by an expert. Although such manual detections have many advantages, some amount of human error is also incorporated. Moreover, expert opinions may vary significantly.
Marek Pecha +4 more
doaj +1 more source
Research on K-Value Selection Method of K-Means Clustering Algorithm
ET Journal, 2019 Among many clustering algorithms, the K-means clustering algorithm is widely used because of its simple algorithm and fast convergence. However, the K-value of clustering needs to be given in advance and the choice of K-value directly affect the ...
Chunhui Yuan, Hai-Tao Yang
semanticscholar +1 more source
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 The Lloyd-Max algorithm is a classical approach to perform K-means clustering. Unfortunately, its cost becomes prohibitive as the training dataset grows large. We propose a compressive version of K-means (CKM), that estimates cluster centers from a sketch, i.e. from a drastically compressed representation of the training dataset.
Keriven, Nicolas +3 more
openaire +5 more sources
Deep k-Means: Jointly clustering with k-Means and learning representations
Pattern Recognition Letters, 2020 Under consideration at Pattern Recognition ...
Moradi Fard, Maziar +2 more
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JOIV: International Journal on Informatics Visualization, 2023 The menu is one of the most fundamental aspects of business continuity in the culinary industry. One of the tools that can be used for menu analysis is menu engineering.
Nina Setiyawati +2 more
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K−Means Clustering Microaggregation for Statistical Disclosure Control
, 2012 This paper presents a K-means clustering technique that satisfies the bi-objective function to minimize the information loss and maintain k-anonymity. The proposed technique starts with one cluster and subsequently partitions the dataset into two or more
Abdun Naser Mahmood +5 more
core +1 more source