2024
DOI: 10.3934/dsfe
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Development and application of machine learning models in US consumer price index forecasting: Analysis of a hybrid approach

Yunus Emre Gur

Abstract: <p>This study aims to apply advanced machine-learning models and hybrid approaches to improve the forecasting accuracy of the US Consumer Price Index (CPI). The study examined the performance of LSTM, MARS, XGBoost, LSTM-MARS, and LSTM-XGBoost models using a large time-series data from January 1974 to October 2023. The data were combined with key economic indicators of the US, and the hyperparameters of the forecasting models were optimized using genetic algorithm and Bayesian optimization methods. Accor… Show more

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