An improved K‐means algorithm for big data

Abstract An improved version of K‐means clustering algorithm that can be applied to big data through lower processing loads with acceptable precision rates is presented here. In this method, the distances from one point to its two nearest centroids were used along with their variations in the last t...

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Bibliographic Details
Main Authors: Fatemeh Moodi, Hamid Saadatfar
Format: Article
Language:English
Published: Wiley 2022-02-01
Series:IET Software
Subjects:
Online Access:https://doi.org/10.1049/sfw2.12032
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