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- W3155369511 abstract "Credit scoring is a classification task from the machine learning perspective. Efficiently classifying bad borrowers is the main aim of building a credit scoring model. This work proposes a novel adaptive softmax regression method for credit scoring. We augment a simple softmax regression by deep neural networks to make its estimated probabilities as an adaptive for each observation. Our experimental result on public benchmark datasets shows that adaptive softmax regression outperformed the machine learning baselines in terms of Brier score, area under the curve (AUC) and accuracy." @default.
- W3155369511 created "2021-04-26" @default.
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- W3155369511 date "2021-01-01" @default.
- W3155369511 modified "2023-09-23" @default.
- W3155369511 title "Adaptive Softmax Regression for Credit Scoring" @default.
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- W3155369511 doi "https://doi.org/10.1007/978-981-33-6757-9_51" @default.
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