<?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>随机森林 on s-ai-unix's Blog</title><link>https://s-ai-unix.github.io/tags/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/</link><description>Recent content in 随机森林 on s-ai-unix's Blog</description><generator>Hugo -- 0.161.1</generator><language>zh-cn</language><lastBuildDate>Thu, 29 Jan 2026 08:11:01 +0800</lastBuildDate><atom:link href="https://s-ai-unix.github.io/tags/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/index.xml" rel="self" type="application/rss+xml"/><item><title>决策树及其衍生算法：从ID3到现代梯度提升</title><link>https://s-ai-unix.github.io/posts/2026-01-29-decision-trees-and-beyond-from-id3-to-modern-gradient-boosting/</link><pubDate>Thu, 29 Jan 2026 08:11:01 +0800</pubDate><guid>https://s-ai-unix.github.io/posts/2026-01-29-decision-trees-and-beyond-from-id3-to-modern-gradient-boosting/</guid><description>系统综述决策树算法及其衍生方法：从经典ID3、C4.5、CART到现代随机森林、XGBoost、LightGBM，深入浅出揭示树模型的数学原理与应用实践</description></item></channel></rss>