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		<title>New Feature Selection Method Prods Probability Densities to Reveal Which Data Features Matter</title>
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		<pubDate>Sat, 10 Oct 2026 10:42:28 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Bioinformatics]]></category>
		<category><![CDATA[class overlap]]></category>
		<category><![CDATA[Explainable AI]]></category>
		<category><![CDATA[Feature Selection]]></category>
		<category><![CDATA[filter methods]]></category>
		<category><![CDATA[high-dimensional data]]></category>
		<category><![CDATA[human-in-the-loop]]></category>
		<category><![CDATA[kernel density estimation]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[niche overlap coefficient]]></category>
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					<description><![CDATA[Researchers have developed ProD, a visualizable filter feature selection method that ranks variables by measuring the geometric overlap between class probability densities.]]></description>
		
		
		
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