Evaluation System on Public Entrepreneurship and Innovation Based on Machine Learning postprint

Abstract: [Purpose/significance] Based on the open data related to scientific and technological innovation, this paper establishes the evaluation system and index for public entrepreneurship and innovation of the cities in China. [Method/process] By the machine learning algorithm, this paper established the Double-Innovation rank of domestic cities, and analyzed the Double-Innovation ability of the cities through various indicators and urban agglomeration characteristics. [Result/conclusion] The results show that the level of DoubleInnovation in our country is closely related to economic resources, talent pool and policy environment. Beijing continues to lead Chinese dual-development, and the regional central cities are closely following it, these cities have their own advantages, and the development gap among them is small. The shortcomings of each city are also very clear. How to make reasonable countermeasures against their respective shortcomings, make up for the weaknesses, is the basis for the continuous development of urban innovation.