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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>The Data Replication Method for the Classification with Reject Option · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1011.3177/</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/1011.3177/feed.xml" rel="self" type="application/rss+xml" /><item><title>The Data Replication Method for the Classification with Reject Option — mentioned by JD557</title><link>https://news.ycombinator.com/item?id=18552900</link><guid isPermaLink="false">urn:hackerpapers:mention:1011.3177:18552900</guid><pubDate>Wed, 28 Nov 2018 16:34:39 GMT</pubDate><description>&lt;p&gt;My Master thesis supervisor had a fun trick for this, that can be used not only on on NNs, but also on other classifiers: https://arxiv.org/pdf/1011.3177.pdf The gist is, you train a single classifier that will work as two classifiers (with certain restrictions): one that says &amp;quot;false/not-false&amp;quot; and another that says &amp;quot;true/not-true&amp;quot;. If the output of the classifier is &amp;quot;not-false&amp;quot; and &amp;quot;not-true&amp;quot;, then you consider that as a &amp;quot;I don&amp;#x27;t know&amp;quot;.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1011.3177/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
