<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Shapley - 标签 - Victor's Code Journey</title><link>http://www.victorchu.info/tags/shapley/</link><description>Shapley - 标签 - Victor's Code Journey</description><generator>Hugo -- gohugo.io</generator><language>zh-cn</language><managingEditor>victorchu0610@outlook.com (victorchutian)</managingEditor><webMaster>victorchu0610@outlook.com (victorchutian)</webMaster><lastBuildDate>Thu, 05 Nov 2026 15:00:00 +0800</lastBuildDate><atom:link href="http://www.victorchu.info/tags/shapley/" rel="self" type="application/rss+xml"/><item><title>多因素叠加归因：Shapley 值与多触点权重</title><link>http://www.victorchu.info/posts/2026/11/961422de/</link><pubDate>Thu, 05 Nov 2026 15:00:00 +0800</pubDate><author><name>victorchutian</name></author><guid>http://www.victorchu.info/posts/2026/11/961422de/</guid><description>&lt;div class="featured-image">
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            &lt;/div>多个因素同时作用于一个结果、且写不出显式函数时，Shapley 值用边际贡献在所有加入顺序上的加权平均来分配功劳。本文从合作博弈讲起，给出可运行的枚举实现与蒙特卡洛近似，并说明多触点权重分配与它的关系。</description></item></channel></rss>