<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Model Design on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/model-design/</link><description>Recent content in Model Design 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/model-design/index.xml" rel="self" type="application/rss+xml"/><item><title>Inductive Bias</title><link>https://terms-en.ai-term-hub.com/en/terms/inductive_bias/</link><pubDate>Sat, 18 Jul 2026 10:02:49 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/inductive_bias/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Inductive bias represents the inherent preferences or constraints built into a machine learning model that allow it to generalize from training data to unseen data. Without such biases, a model cannot distinguish between valid patterns and noise. In the context of ethics and safety, understanding inductive bias is crucial because biased assumptions can lead to discriminatory outcomes or unfair predictions, necessitating careful auditing and mitigation strategies to ensure equitable AI behavior.&lt;/p></description></item></channel></rss>