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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1908.05376/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1908.05376/feed.xml" rel="self" type="application/rss+xml" /><item><title>Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform — HN submission</title><link>https://news.ycombinator.com/item?id=36484868</link><guid isPermaLink="false">urn:hackerpapers:submission:1908.05376:36484868</guid><pubDate>Mon, 26 Jun 2023 19:50:11 GMT</pubDate><description>&lt;p&gt;Maximum Relevance and Minimum Redundancy Feature Selection Methods&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1908.05376/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
