Results 61 to 70 of about 940,524 (345)
Comprehensive Review of K-Means Clustering Algorithms
International Journal of Advances in Scientific Research and Engineering, 2021 This paper presents a comprehensive review of existing techniques of k-means clustering algorithms made at various times. The k-means algorithm is aimed at partitioning objects or points to be analyzed into well-separated clusters.
Eric U. Oti +3 more
semanticscholar +1 more source
Clustering Affine Subspaces: Algorithms and Hardness [PDF]
, 2012 We study a generalization of the famous k-center problem where each object is an affine subspace of dimension Δ, and give either the first or significantly improved algorithms and hardness results for many combinations of parameters.
Lee, Euiwoong
core +1 more source
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
Analyze the Clustering and Predicting Results of Palm Oil Production in Aceh Utara
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023 PT. Perkebunan Nusantara 1 is engaged in oil palm production with a total land area of 1,144 Ha. The formulation of this research can determine productive land clusters based on land area, number of trees, number of stages, and palm oil production ...
Mutammimul Ula +3 more
doaj +1 more source
On Variants of k-means Clustering
CoRR, 2015 15 ...
Bandyapadhyay, Sayan +1 more
openaire +4 more sources
A Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho +7 more
wiley +1 more source
, 2023 This paper presents two novel deterministic initialization procedures for k-means clustering based on a modified crowding distance. The procedures, named ck-means and fck-means, use more crowded points as initial centroids.
Abdesslem Layeb
core +1 more source
Application of Machine Learning-Based K-means Clustering for Financial Fraud Detection
Academic Journal of Science and TechnologyIn today's increasingly digital financial landscape, the frequency and complexity of fraudulent activities are on the rise, posing significant risks and losses for both financial institutions and consumers.
Zengyi Huang +3 more
semanticscholar +1 more source
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Clustering Library Loan Books Using K-Means Clustering
Journal of Information Systems and InformaticsOptimal library collection management requires an understanding of book borrowing patterns to align availability with user needs. Without proper analysis, less popular books may remain in large quantities, while popular books may experience shortages ...
Mawar Indah Tanjung, Sriani Sriani
doaj +1 more source