<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>无监督学习 on PlumePHP</title><link>https://plumephp.com/tags/%E6%97%A0%E7%9B%91%E7%9D%A3%E5%AD%A6%E4%B9%A0/</link><description>Recent content in 无监督学习 on PlumePHP</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Thu, 13 Aug 2026 11:03:00 +0800</lastBuildDate><atom:link href="https://plumephp.com/tags/%E6%97%A0%E7%9B%91%E7%9D%A3%E5%AD%A6%E4%B9%A0/index.xml" rel="self" type="application/rss+xml"/><item><title>03. 无监督学习与降维</title><link>https://plumephp.com/ai-unsupervised-learning/</link><pubDate>Thu, 13 Aug 2026 11:03:00 +0800</pubDate><guid>https://plumephp.com/ai-unsupervised-learning/</guid><description>&lt;p&gt;无监督学习处理没有标签的数据，旨在发现隐藏的数据结构和模式。本文涵盖聚类、降维与关联规则三大方向的核心算法。&lt;/p&gt;
&lt;h2 id="1-聚类-clustering"&gt;1. 聚类 (Clustering)&lt;/h2&gt;
&lt;p&gt;聚类将相似的数据点分到同一组。关键在于定义&amp;quot;相似性&amp;quot;和&amp;quot;簇的形状&amp;quot;。&lt;/p&gt;</description></item></channel></rss>