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	<title>out-of-time validation &#8211; BIOENGINEER.ORG</title>
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		<title>Turning Loan Data Into Images Helps AI Predict Peer-to-Peer Credit Defaults</title>
		<link>https://bioengineer.org/turning-loan-data-into-images-helps-ai-predict-peer-to-peer-credit-defaults/</link>
		
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		<pubDate>Sat, 10 Oct 2026 18:35:01 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[convolutional neural network]]></category>
		<category><![CDATA[credit default prediction]]></category>
		<category><![CDATA[data leakage]]></category>
		<category><![CDATA[feature-to-image encoding]]></category>
		<category><![CDATA[IGTD]]></category>
		<category><![CDATA[LendingClub]]></category>
		<category><![CDATA[LightGBM]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[out-of-time validation]]></category>
		<category><![CDATA[peer-to-peer lending]]></category>
		<category><![CDATA[Random Forest]]></category>
		<category><![CDATA[XGBoost]]></category>
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					<description><![CDATA[Researchers converted millions of LendingClub loan records into structure-aware grayscale images and showed that a hybrid convolutional neural network and Random Forest model predicts peer-to-peer credit defaults more accurately and more robustly than conventional tabular machine learning models.]]></description>
		
		
		
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