M.S. THESIS PRESENTATION Title: Meal Participation Prediction with Bayesian Hierarchical Models
Time: 31 Dec 2021 01:30 ÖS İstanbul
https://zoom.us/j/6547746234?pwd=ZENZNWtCbUlQRjVMMVFneWtxZGlzZz09
Meeting ID: 654 774 6234
Pasword: 478379
Abstract:
Forecasting sales in the catering industry helps authorities to organize daily trans - actions efficiently to prevent both waste and business loss. In this study, we focused on predicting meal sales in Bilintur Catering Centre with the dataset collected for five academic years. To forecast the meal sales, we constructed two Bayesian hierarchical models. The first model does not differentiate effects of predictors in different academic years, while the second does. We derived the full conditional distributions and employed Gibbs sampling in an extensive MCMC study. We tested two models along with a benchmark multiple regression model on the held-out academic year. We concluded that the effects of certain predictors change over time, hierarchical Bayes models can depict the change, and the natural regularization property of Bayesian approach gives more accurate and stable forecasts.
