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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>Density-Based Clustering - Glosarix</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="7FwhiTmgSZ"&gt;&lt;a href="https://glosarix.com/en/glossary/density-based-clustering-en/"&gt;Density-Based Clustering&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/density-based-clustering-en/embed/#?secret=7FwhiTmgSZ" width="600" height="338" title="&#x201C;Density-Based Clustering&#x201D; &#x2014; Glosarix" data-secret="7FwhiTmgSZ" 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: Density-based clustering is an unsupervised learning approach that groups data based on the density of points in space. This method identifies dense regions of data and groups them, while points found in low-density areas are considered noise or outliers. Unlike other clustering methods, such as k-means, which require the number of clusters to be [&hellip;]</description></oembed>
