Predicting China's Economic Running State Using Machine Learning

¹ School of Science, Jimei University, Xiamen, Fujian, 361021, China
² Computer engineering college, Jimei University , Xiamen, Fujian, 361021, China

^a Corresponding author: yonggangfu@jmu.edu.cn

Abstract

China's business index of macro-economic includes early warning index, coincidence index, leading index and lagging index, among which early warning index reflects the economic running state. However, obtaining these indexes is a complex and daunting task. To simplify the task, this article mainly explores how to use machine learning algorithms including multiple linear regression (MLR), support vector machine regression (SVM), random forest (RF), artificial neural network (ANN) and extreme learning machine (ELM) to accurately predict early warning index. Finally, it can be found that the warning index can be well predicted by above machine learning algorithms with coincidence index, leading index and lagging index to be variables, furthermore, extreme learning machine and random forest are superior to other methods.