<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[RSS Feed]]></title><description><![CDATA[RSS Feed]]></description><link>https://ecency.com</link><image><url>https://ecency.com/logo512.png</url><title>RSS Feed</title><link>https://ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Sun, 13 Sep 2026 03:59:53 GMT</lastBuildDate><atom:link href="https://ecency.com/created/gaussiannb/rss.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[1-19 GaussianNB Classification]]></title><description><![CDATA[GaussianNB Classifier 를 사용해 보기 전에 5-0 Bayesian Rule 과 기초 확률론내용을 사전에 살펴보도록 하자. GaussianNB 는 Naive Baesian 알고리듬의 특수한 경우이다. 즉 학습과 테스트를 위한 샘플들이 연속적인 변수일 때 사용하는 알고리듬으로서 Scikit-learn의 상당 수 알고리듬들이 인식율을 높이기 위해]]></description><link>https://ecency.com/@codingart/1-19-gaussiannb-classification</link><guid isPermaLink="true">https://ecency.com/@codingart/1-19-gaussiannb-classification</guid><category><![CDATA[kr]]></category><dc:creator><![CDATA[codingart]]></dc:creator><pubDate>Mon, 05 Aug 2019 13:51:15 GMT</pubDate><enclosure url="https://i.ecency.com/p/HNWT6DgoBc14riaEeLCzGYopkqYBKxpGKqfNWfgr368M9Wbxi7jpcLMoz7i1daw53UstT8yqSjKr8wids6Wuh7Ap8REoJ5kfMdK989dDH9x3ar1SwMsns1qt7tA?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>