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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DeBaCl: A Python Package for Interactive DEnsity-BAsed CLustering · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1307.8136/</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/1307.8136/feed.xml" rel="self" type="application/rss+xml" /><item><title>DeBaCl: A Python Package for Interactive DEnsity-BAsed CLustering — mentioned by ihartley</title><link>https://news.ycombinator.com/item?id=10643054</link><guid isPermaLink="false">urn:hackerpapers:mention:1307.8136:10643054</guid><pubDate>Sat, 28 Nov 2015 23:49:28 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;m reading through the paper on DeBaCl right now which might be a little more accessible than the paper you found. I think the gist of it is that Level set trees offer better theoretical guarantees due to other methods being less rigorous with their theory. http://arxiv.org/pdf/1307.8136v1.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1307.8136/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ME</category></item></channel></rss>
