Results 31 to 40 of about 1,835,018 (264)
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
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
doaj +1 more source
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
doaj +1 more source
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 +3 more sources
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 +3 more sources
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
doaj +1 more source
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
openaire +4 more sources
A parametric k-means algorithm [PDF]
Computational Statistics, 2007 The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution.
openaire +4 more sources
Soil data clustering by using K-means and fuzzy K-means algorithm
Telfor Journal, 2016 A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering.
E. Hot, V. Popović-Bugarin
doaj +1 more source
Penerapan Algoritma K-Means Untuk Mengklasifikasi Data Obat
Jurnal Sisfokom, 2023 Pengklasifikasian data obat pada sebuah instansi yang bergerak pada bidang Kesehatan merupakan hal yang sangat penting. Kegiatan tersebut tidak lepas dari pengawasan serta monitoring setiap harinya karena pengolahan data obat termasuk inti dalam ...
Ferdy Pangestu Ferdy Pangestu +3 more
doaj +1 more source