Pet Food Market Analysis and Prediction Based on Multiple Regression and Machine Learning Technology

Abstract

This study focuses on the pet food market, aiming to analyze the development trend and influencing factors of the Chinese and global markets, and make accurate forecasts. For the Chinese market, we collected historical data and used linear regression and multiple regression models incorporating social factors to analyze changes in market size and pet number in the past five years and forecast trends in the next three years. In the global market research, data conversion, feature extraction, random forest model and other technologies are used to predict the demand and market size of pet food in different countries by combining population characteristics and pet consumption data. The study found that the scale of China's pet market will grow but the growth rate will be slow, the number of cats will increase, and the number of dogs will be relatively stable; Global markets have performed differently. This study provides decision support for enterprises and policy makers, helps the industry cope with market changes and policy adjustments, and explores sustainable development paths.