Using Machine Learning Method to Qualify and Evaluate the Regional Economy

Abstract

As the economic lifeline of Southwest China, Sichuan Province has contributed to Chinese sustainable economic development, the most prominent Chengdu. Chengdu-Chongqing area has been pivotal in China's regional development plate. In the 14th Five-Year Plan of China, the implementation of the Chengdu-Chongqing double cities economic circle is emphasized from different aspects. This policy can directly stimulate the regional economy, thus driving the economic development of Sichuan. Accordingly, the study takes the GDP in 2018 of 21 cities of Sichuan province as the dependent variable. Except for the traditional financial method or model, the study adopts one of the Machine Learning methods, Principal Component Analysis (PCA), to compare the development level of 21 cities horizontally and vertically. Meanwhile, within the Machine Learning method, the new model's sampling accuracy is 0.803, and the first two principal components could interpret 91.206% of the total variance. Therefore, the study evaluates, analyzes the results of new ranks of 21 cities, exploring the possibility of coordinated economic development of Sichuan province under the background of the construction of twins "Chengdu-Chongqing economic circle." Hopefully, the consequence of research provides a theoretical reference for the policy implementation.