English(EN) Assessing the impact of dimensionality reduction on clustering performance -- a systematic study

研究系统评估降维对聚类性能的影响

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-27 04:00

一项新研究系统地评估了五种不同的降维技术如何影响四种常用聚类算法的性能。研究人员发现，降维方法的选择和降维程度对聚类质量有显著影响。研究结果强调，最佳设置取决于具体的数据几何形状和所选的聚类方法。 AI

影响对降维方法在聚类中的应用进行了系统性比较，为数据科学家提供了指导。

排序理由在arXiv上发表的关于机器学习技术的学术论文。

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arXiv cs.LG TIER_1 English(EN) · Ousmane Assani Amate, Mohammadreza Bakhtyari, \'Emilie Roy, Vladimir Makarenkov · 2026-04-27 04:00

降维对聚类性能影响的评估——一项系统性研究

arXiv:2604.22099v1 Announce Type: new Abstract: Dimensionality reduction is a critical preprocessing step for clustering high-dimensional data, yet comprehensive evaluation of its impact across diverse methods and data types remains limited. In this study, we systematically asses…