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<oembed><version>1.0</version><provider_name>Glosarix</provider_name><provider_url>https://glosarix.com/en/</provider_url><author_name>Team Glosarix</author_name><author_url>https://glosarix.com/en/author/adm_glosarix/</author_url><title>Model Evaluation - Glosarix</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="hyQ5GY0QlJ"&gt;&lt;a href="https://glosarix.com/en/glossary/model-evaluation-en/"&gt;Model Evaluation&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/model-evaluation-en/embed/#?secret=hyQ5GY0QlJ" width="600" height="338" title="&#x201C;Model Evaluation&#x201D; &#x2014; Glosarix" data-secret="hyQ5GY0QlJ" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Description: Model evaluation is the process of measuring and analyzing the performance of a machine learning model to determine its effectiveness for the specific task it was designed for. This process involves using quantitative and qualitative metrics that allow developers and data scientists to understand how the model behaves against test data that was not [&hellip;]</description></oembed>
