<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Probability-Calibration on DATATWEETS</title><link>https://datatweets.com/tags/probability-calibration/</link><description>Recent content in Probability-Calibration on DATATWEETS</description><generator>Hugo</generator><language>en</language><copyright>Copyright (c) 2026 Datatweets</copyright><lastBuildDate>Tue, 14 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://datatweets.com/tags/probability-calibration/index.xml" rel="self" type="application/rss+xml"/><item><title>Calibrate Gradient Boosting Probabilities in Python</title><link>https://datatweets.com/tutorials/calibrate-gradient-boosting-probabilities-python/</link><pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate><guid>https://datatweets.com/tutorials/calibrate-gradient-boosting-probabilities-python/</guid><description>A beginner-friendly guide to checking whether classifier probabilities match observed rates, then correcting overconfident gradient boosting predictions with cross-validated sigmoid calibration.</description></item></channel></rss>