<?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>EM 알고리즘 on qofo.log</title><link>https://qofo.github.io/tags/em-%EC%95%8C%EA%B3%A0%EB%A6%AC%EC%A6%98/</link><description>Recent content in EM 알고리즘 on qofo.log</description><generator>Hugo</generator><language>ko-KR</language><lastBuildDate>Mon, 12 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://qofo.github.io/tags/em-%EC%95%8C%EA%B3%A0%EB%A6%AC%EC%A6%98/index.xml" rel="self" type="application/rss+xml"/><item><title>MML 11장 GMM: 가우시안 혼합 모델과 EM 알고리즘</title><link>https://qofo.github.io/posts/mml-ch11-gmm-em/</link><pubDate>Mon, 12 Oct 2026 00:00:00 +0000</pubDate><guid>https://qofo.github.io/posts/mml-ch11-gmm-em/</guid><description>MML 11장(교재 348~369쪽) 해설. 가우시안 혼합 모델의 최대가능도 학습, 책임도 계산과 평균·공분산·가중치 갱신식 유도, EM 알고리즘 한 바퀴 손계산, 잠재변수 관점을 정리했다.</description></item></channel></rss>