Prediction for Türkiye’s Tea Product With Machine Learning Algorithms

Abstract

This study predicts tea production in Turkey using machine learning algorithms. The analysis utilized data from 2001 to 2022, including tea production quantity, fresh tea prices, tea production area, temperature, and humidity. The study was conducted using the MATLAB 2023b Regression Learner toolbox. Initially, the obtained data were normalized, and then prediction performances were evaluated using various machine learning algorithms. The metrics used in the study included R², MAE, RMSE, and MSE. As a result, the Gaussian Process Regression algorithm emerged as the best-performing machine learning method