One-dimensional convolutional neural networks with feature selection for highly concise rule extraction from credit scoring datasets with heterogeneous attributes

Y Hayashi, N Takano - Electronics, 2020 - mdpi.com
Convolution neural networks (CNNs) have proven effectiveness, but they are not applicable
to all datasets, such as those with heterogeneous attributes, which are often used in the …

Does deep learning work well for categorical datasets with mainly nominal attributes?

Y Hayashi - Electronics, 2020 - mdpi.com
Given the complexity of real-world datasets, it is difficult to present data structures using
existing deep learning (DL) models. Most research to date has concentrated on datasets …

Credit scoring using neural networks and SURE posterior probability calibration

M Garcin, S Stéphan - arXiv preprint arXiv:2107.07206, 2021 - arxiv.org
In this article we compare the performances of a logistic regression and a feed forward
neural network for credit scoring purposes. Our results show that the logistic regression …

Cascade of Deep Neural Network And Support Vector Machine for Credit Risk Prediction

O Awodele, S Alimi, O Ogunyolu… - 2022 5th Information …, 2022 - ieeexplore.ieee.org
One of the core financial services that banks render to their customers is granting of loans
with interest over a period. To minimize the risk of loan default which eventually may lead to …

[PDF][PDF] CASCADE OF DEEP NEURAL NETWORK AND SUPPORT VECTOR MACHINE FOR CREDIT RISK PREDICTION

S Alimi, O Ogunyolu, O Solanke, S Iyawe, F Adegbie - researchgate.net
One of the core financial services that banks render to their customers is granting of loans
with interest over a period. To minimize the risk of loan default which eventually may lead to …