<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Multi-Dimensional Scaling - Tag - Zhiverse</title><link>https://yao-chih.netlify.app/en/tags/multi-dimensional-scaling/</link><description>Multi-Dimensional Scaling - Tag - Zhiverse</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>yaochihh@gmail.com (Josh)</managingEditor><webMaster>yaochihh@gmail.com (Josh)</webMaster><copyright>Zhiverse</copyright><atom:link href="https://yao-chih.netlify.app/en/tags/multi-dimensional-scaling/" rel="self" type="application/rss+xml"/><item><title>Multi-dimensional Scaling</title><link>https://yao-chih.netlify.app/en/multi-dimensional-scaling/</link><pubDate>Thu, 15 May 2025 15:58:34 +0800</pubDate><author>Author</author><guid>https://yao-chih.netlify.app/en/multi-dimensional-scaling/</guid><description>&lt;div class="featured-image">
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            &lt;/div>Multi-dimensional Scaling (MDS) is a dimensionality reduction technique that calculates pairwise distances between objects in a dataset and represents them in a lower-dimensional space while preserving the original relative distance structure. MDS can be seen as a method for visualizing data to intuitively observe the relative relationships between data points.</description></item></channel></rss>