Results 41 to 50 of about 15,852,135 (305)
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
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Detecting Learning Patterns in Tertiary Education Using K-Means Clustering
Information, 2022 We are in the era where various processes need to be online. However, data from digital learning platforms are still underutilised in higher education, yet, they contain student learning patterns, whose awareness would contribute to educational ...
Emmanuel Tuyishimire +3 more
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, 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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Metode Elbow dalam Optimasi Jumlah Cluster pada K-Means Clustering
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, 2023 K-Means clustering merupakan salah satu strategi yang digunakan dalam analisis data dan machine learning untuk mengelompokkan data menjadi beberapa kelompok (cluster) berdasarkan kemiripan fitur atau atributnya.
Nadia Annisa Maori, Evanita Evanita
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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
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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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RSKC: An R Package for a Robust and Sparse K-Means Clustering Algorithm
Journal of Statistical Software, 2016 Witten and Tibshirani (2010) proposed an algorithim to simultaneously find clusters and select clustering variables, called sparse K-means (SK-means).
Yumi Kondo +2 more
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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
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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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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
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