9th International Conference on ICT for Sustainable Development

Authors - Laksh Doshi, Jay Samberkar, Chaitanya Deshpande, Kumkum Saxena
Abstract - The valuation of the sneaker resale industry has reached a mark of about $13.37 billion in 2024 and it is assured to reach a mark of $30 billion by 2030. This has a simple indication that the growth in the sale of the sneakers has become a powerful business opportunity. E-commerce giants have emerged in the sneaker resale market like StockX and GOAT. Sneaker resale price prediction can help small scale resellers and buyers. The aim of this research is to compare the performance of different machine learning algorithms and find out the best model for the prediction of the resale price of the sneakers. The machine learning models used in this study are Linear Regression, Random Forest Regressor, Lasso Regression, followed by the ensemble learning methods – bagging and stacking. All the three base models give similar performance with lasso having slight edge. Further research shows that stacking using lasso regression with base model lasso regression gives the best result.