Conveners
ISBIS Invited Session
- Matilde Bini (European University of Rome)
The increased use of random forest (RF) methods as a supervised statistical learning technique is primarily attributed to their simplicity and ability to handle complex datasets. A RF consists of multiple decision trees, which can be categorized into two types based on how they process node splitting: parallel and oblique. Axes-parallel decision trees split the feature space using a single...
In this study, we investigate the economic impact of COVID-19 on employment within Italian firms. In particular, we analyse how employment levels were affected across different types of firms and assess the extent of the impact. We also examine the role of public subsidies provided during the COVID-19 period and evaluate the occupational mix between ‘flexible’ and ‘non-flexible’ employees....
This study focuses on bankruptcy prediction for micro-sized enterprises, a segment often overlooked in credit risk modeling due to the limited reliability of their financial data. Building on prior research that highlights the importance of sector-specific strategies, we construct separate predictive models for selected industries using a dataset of 84,019 Italian micro-enterprises, of which...