Market Trend Prediction of Digital Economy Based on Machine Learning Algorithm

Abstract

The focus of digitization on helping enterprises, organisations, and governments accomplish their sustainability goals is a defining feature of the contemporary economic landscape. Machine Learning has recently been included into company models and plans along with the use of the newest technology, which has allowed the environment for business in the digital economy will get even better. The digital economy is extensively covered, extremely innovative, and highly porous. It serves as both a fresh hub for economic growth and a pivot for modernising and changing established sectors. The digital economy has the power to provide new employment opportunities, increase consumer demand, and boost investment activity. It is a crucial component in building a contemporary economic structure. Based on data pertaining to the raise of the digital economy in Zhejiang Province, China, between 2014 and 2023, this study finds that taking two samples—the bare minimum needed for node splitting—gets the best results. The research data is then analysed to create a Multi Linear based Random Forest Regression Algorithm (ML-RFR), where training data comprises 70% and testing data has 30%. The study concluded that rather than heedlessly following economic trends, the expansion of the digital economy necessitates raising the standard of the sector's digital economy, extending its level of development, and optimising its development model.