random forest, logistic regression, and artificial neural networks. The SMOT technique was used to balance the dataset ….03%, specificity of 80%, and an AUC of 90.00%. Logistic regression resulted in an accuracy of 80.36%, 97.62% precision, 80.39% recall … substantial financial challenge. Therefore, supervised machine and deep learning analytics such as random forest, logistic …

dataset of 1883 Russian firms from 2013 to 2021, this research employs logistic regression to identify factors that promote …

between the CTN and LP were determined by multinomial logistic regression analysis (MLRA). According to the findings, as the …

supporting green business initiatives. This study uses backward logistic regression analysis to identify variables affecting …

borrowers. The binary logistic regression result revealed that loan repayment period, grace period, and timeliness of loan …