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	<title>feature construction &#8211; Penn AI Tech</title>
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	<title>feature construction &#8211; Penn AI Tech</title>
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		<title>Feature Inclusion Bin Evolver for Risk Stratification (FIBERS)</title>
		<link>https://resources.pennaitech.org/feature-inclusion-bin-evolver-for-risk-stratification-fibers/</link>
		
		<dc:creator><![CDATA[Ray]]></dc:creator>
		<pubDate>Sun, 05 Mar 2023 20:50:27 +0000</pubDate>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Feature learning]]></category>
		<category><![CDATA[Technology: Tools, Hardware, and Software]]></category>
		<category><![CDATA[All Resources]]></category>
		<category><![CDATA[feature engineering]]></category>
		<category><![CDATA[binning]]></category>
		<category><![CDATA[feature learning]]></category>
		<category><![CDATA[code]]></category>
		<category><![CDATA[software]]></category>
		<category><![CDATA[feature construction]]></category>
		<guid isPermaLink="false">https://resources.pennaitech.org/?p=218</guid>

					<description><![CDATA[FIBERS is an evolutionary algorithm for performing feature learning by binning features to stratify risk in biomedical datasets with either a binary outcome or with right censored survival outcomes over time. &#160;]]></description>
										<content:encoded><![CDATA[<p><span style="font-weight: 400">FIBERS is an evolutionary algorithm for performing feature learning by binning features to stratify risk in biomedical datasets with either a binary outcome or with right censored survival outcomes over time.</span></p>
<p>&nbsp;</p>
]]></content:encoded>
					
		
		
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		<title>Multifactor Dimensionality Reduction (scikit-MDR)</title>
		<link>https://resources.pennaitech.org/multifactor-dimensionality-reduction-scikit-mdr/</link>
		
		<dc:creator><![CDATA[Ray]]></dc:creator>
		<pubDate>Sun, 05 Mar 2023 20:51:58 +0000</pubDate>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Feature learning]]></category>
		<category><![CDATA[Technology: Tools, Hardware, and Software]]></category>
		<category><![CDATA[All Resources]]></category>
		<category><![CDATA[feature construction]]></category>
		<category><![CDATA[feature engineering]]></category>
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		<category><![CDATA[software]]></category>
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		<guid isPermaLink="false">https://resources.pennaitech.org/?p=220</guid>

					<description><![CDATA[A scikit-learn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction. This project is still under active development and we encourage you to check back on this repository regularly for updates. MDR is an effective feature construction algorithm that &#8230; <a class="kt-excerpt-readmore more-link" href="https://resources.pennaitech.org/multifactor-dimensionality-reduction-scikit-mdr/">Read More</a>]]></description>
										<content:encoded><![CDATA[<p><span style="font-weight: 400">A scikit-learn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction. This project is still under active development and we encourage you to check back on this repository regularly for updates. MDR is an effective feature construction algorithm that is capable of modeling higher-order interactions and capturing complex patterns in data sets. MDR currently only works with categorical features and supports both binary classification and regression problems. We are working on expanding the algorithm to cover more problem types and provide more convenience features.</span></p>
<p>&nbsp;</p>
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