Research On County Economic Development Of Shandong Province Based On Random Forest Algorithm

The 19th National Congress of the Communist Party of China proposed the implementation of the strategy of rural revitalization,which has far-reaching significance for the further integration of urban-rural relations and urbanization in China.As a major economic province in Shandong Province,it is the current focus of work to promote high-quality development,actively promote the conversion of old and new kinetic energy,and revitalize the countryside.In response to the strategy of rural revitalization,the provincial government clearly stated in the work report that "building a Qilu model for rural revitalization from a high starting point",an important part of which is to study and formulate a Qilu model standard system for rural revitalization,and explore the classification and promotion mechanism for rural revitalization in the eastern,central and western regions Create a unique modern version of "Fuchun Mountain Residence".Therefore,how to examine the comprehensive performance of the economic development of various counties in Shandong Province from multiple angles,and to divide the level of county economic development more reasonably,is particularly important.Based on the systematic review of the research on the evaluation of county economic development by scholars at home and abroad.this paper combines the actual development of county economy in Shandong Province,builds an evaluation sy stem of county economic development in Shandong Province,introduces a random forest algorithm model to filter variables,and conducts a county economic development evaluation.Evaluation forecast.This article systematically explains the principles of the random forest algorithm,and details the advantages of the random forest algorithm in handling nonlinear,high-dimensional,high-noise,and difficult-to-overfit problems.In addition,the function of the algorithm for feature selection based on the error outside the bag is introduced,and a cross-validation method is introduced to improve the effectiveness of feature selection.Based on the sample data of Shandong Province and national counties from 1997 to 2017,the empirical research shows that after selecting the feature variables of the comprehensive sample,the RMSE of the new evaluation model is significantly lower than that of the initial model.Next,after training the algorithm using the data in the sample,the paper predicts the data out of the sample.The prediction results divide the economic development of the county in Shandong Province into three categories,namely high,medium and low growth.Comparing the obtained results with the actual economic development of the county,we can find that the random forest algorithm has a high accuracy rate for the prediction of the economic development of the county,especially in the prediction of high-speed growth of the county.Based on the above empirical results,combined with a detailed analysis of counties with large deviations,the paper provides a reference for implementing the new and old kinetic energy conversion and rural revitalization strategies on the basis of constructing a high-quality evaluation system for county economic development in Shandong Province and improving evaluation methods.Suggest.These include the conversion of old and new kinetic energy in accordance with market laws,eliminating one-size-fits-all;industry introduction should be tailored to local conditions and avoid following the trend;counties should always be vigilant about real estate investment in fixed assets and real estate loans from financial institutions.Taken together,the above research has certain value in both research methods and county economic development practice.The article research has achieved good results.Finally,the paper also prospects the future research direction of county economic development.