Research on Performance Optimization of K-Means Algorithm on Large Dataset
DOI:
https://doi.org/10.53469/wjimt.2025.08(06).01Keywords:
K Means algorithm, Big datasets, Performance optimization, Clustering effect, Computational efficiencyAbstract
This article aims to delve into the performance optimization methods of the K Means algorithm on large datasets, in order to improve its efficiency and accuracy in large-scale data processing. Through theoretical analysis, this article will explore how to optimize the K-Means algorithm to address the challenges it faces on big datasets, in order to meet the current demand for efficient data clustering in the big data era. The article will focus on the basic principles and practical methods of performance optimization, aiming to provide innovative research results for the K Means algorithm in large-scale data processing.
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