<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Quality Control on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/quality-control/</link><description>Recent content in Quality Control on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/quality-control/index.xml" rel="self" type="application/rss+xml"/><item><title>Novelty detection</title><link>https://terms-en.ai-term-hub.com/en/terms/novelty_detection/</link><pubDate>Sat, 18 Jul 2026 10:09:21 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/novelty_detection/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Novelty detection is a machine learning task focused on identifying data points that do not conform to expected behavior or known classes. It typically operates in an unsupervised manner, learning the distribution of normal data during training. When new data arrives, the model flags instances that deviate substantially from this learned norm. This is crucial for anomaly detection in security, fraud prevention, and quality control where rare events must be caught without prior labeled examples.&lt;/p></description></item></channel></rss>