首页|Department of Finance Reports Findings in Machine Learning (Enhancing transparen cy and fairness in automated credit decisions: an explainable novel hybrid machi ne learning approach)
Department of Finance Reports Findings in Machine Learning (Enhancing transparen cy and fairness in automated credit decisions: an explainable novel hybrid machi ne learning approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Glasgow, Unite d Kingdom, by NewsRx journalists, research stated, “This paper uses a generalise d stacking method to introduce a novel hybrid model that combines a one-dimensio nal convolutional neural network 1DCNN with extreme gradient boosting XGBoost. W e compared the predictive accuracies of the proposed hybrid architecture with th ree conventional algorithms-1DCNN, XGBoost and logistic regression (LR) using a dataset of over twenty thousand peer-to-peer (P2P) consumer credit observations. ”
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