<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>GMM on s-ai-unix's Blog</title><link>https://s-ai-unix.github.io/tags/gmm/</link><description>Recent content in GMM on s-ai-unix's Blog</description><generator>Hugo -- 0.161.1</generator><language>zh-cn</language><lastBuildDate>Sat, 24 Jan 2026 18:00:00 +0800</lastBuildDate><atom:link href="https://s-ai-unix.github.io/tags/gmm/index.xml" rel="self" type="application/rss+xml"/><item><title>高斯混合模型：从数据中解构隐藏结构的艺术</title><link>https://s-ai-unix.github.io/posts/2026-01-24-gmm-comprehensive-guide/</link><pubDate>Sat, 24 Jan 2026 18:00:00 +0800</pubDate><guid>https://s-ai-unix.github.io/posts/2026-01-24-gmm-comprehensive-guide/</guid><description>深入探讨机器学习中的核心无监督学习算法 GMM，从高斯分布回顾到 EM 算法的完整推导，从几何直观到实际应用，娓娓道来。</description></item></channel></rss>