.../methodology/approach Financial data of non-financial BSE 500 listed companies from April 1, 2014, to March 31, 2024, was utilized for analysis. The study has compared the prediction and classification rate of Linear Regression (LR), logistic regression, support vector machines, random forests and Deep Belief...

.../approach This research analyzes a panel dataset comprising 752 banks from 95 countries from 2011 to 2020, using ordered logistic regression. Findings The results reveal that corporate governance factors, including board size, board age, and board gender diversity, significantly impact credit ratings...

.../methodology/approach Variable importance may vary with the technique applied. Therefore, different classification techniques, such as logistic regression, partial proportional odds regression, and conditional random forest, have been employed. The analysis relies on the Survey of Health, Ageing...

... been used to differentiate between constrained and unconstrained firms. It uses t-test and logistic regression to draw inferences. Findings In general, firms pursuing ZL policy are financially constrained. However, there is a sub-section of ZL firms found unconstrained with high...