Evaluating the Efficacy of Supervised Machine Learning Models in Inflation Forecasting in Sri Lanka
W M S Bandara,
W A R De Mel
Abstract:This study aims to forecast the inflation rate using supervised machine learning models (SMLM). While SMLMs are widely used in various fields, they have not been widely applied in forecasting inflation rates. Therefore, the main objective of this study is to identify the best model for forecasting inflation among four different SMLMs: LASSO regression (LR), Bayesian Ridge Regression (BRR), Support Vector Machine Regression (SVR), and Random Forest Regression (RFR) models. To achieve this objective, two differe… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.