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Descripción
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| Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace? Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model ... | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Plos One |
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ISSN
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1932-6203 |
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Factor de impacto JCR
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2,806 |
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Información de impacto
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Volumen
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DOI
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Número de revista
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Desde la página
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687 |
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Hasta la página
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695 |
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Mes
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SIN MES |
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Ranking
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