Siddhani Lahori

Machine learning to predict survival of small and medium sized enterprises

Started Jan. 5, 2024

Abstract or project description

The project aims to develop a machine learning model using supervised learning to predict the survival likelihood of small and medium-sized enterprises (SMEs). It encompasses several key stages: firstly, gathering a varied dataset including financial indicators, market analysis, and operational metrics. This data undergoes preprocessing to ensure quality and consistency. Next, predictive models are trained using algorithms such as logistic regression and neural networks. The performance of these models is then evaluated using metrics like accuracy and F1-score through cross-validation techniques. A crucial aspect involves analyzing feature importance to discern the most influential factors contributing to SME survivability. By distilling actionable insights from this analysis, the project can equip entrepreneurs with strategies to mitigate risks and enhance their businesses' resilience.