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	<title>Puma Optimization Algorithm &#8211; BIOENGINEER.ORG</title>
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		<title>Puma-Inspired Algorithm Sharpens Feature Selection for Machine Learning</title>
		<link>https://bioengineer.org/puma-inspired-algorithm-sharpens-feature-selection-for-machine-learning/</link>
		
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		<pubDate>Fri, 09 Oct 2026 09:18:08 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[binary optimization]]></category>
		<category><![CDATA[classification accuracy]]></category>
		<category><![CDATA[Feature Selection]]></category>
		<category><![CDATA[Friedman test]]></category>
		<category><![CDATA[intrusion detection]]></category>
		<category><![CDATA[K-Nearest Neighbour]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[metaheuristics]]></category>
		<category><![CDATA[NSL-KDD]]></category>
		<category><![CDATA[Puma Optimization Algorithm]]></category>
		<category><![CDATA[transfer functions]]></category>
		<category><![CDATA[UNSW-NB15]]></category>
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					<description><![CDATA[Researchers at Yazd University developed a binary version of the Puma Optimization Algorithm that achieved 91.53 percent classification accuracy and outperformed rival metaheuristics on feature selection benchmarks and intrusion detection datasets.]]></description>
		
		
		
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