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Factor Analysis Of Public Governace Score Based On Boosting Regression Tree

Posted on:2018-02-25Degree:MasterType:Thesis
Country:ChinaCandidate:J ShengFull Text:PDF
GTID:2416330518958731Subject:Applied Statistics
Abstract/Summary:PDF Full Text Request
Social public governance score is a very important index of the economic and social development level,as well as the living conditions of people.In the pursuit of sustainable and rapid economic development,the economic development should not be the only indicator of the progress of the city.The public would expect a balance between the ecology and the economic development.It is of great theoretical and practical significance to explore the influencing factors of the social public governance score in addition to the way and the degree of its influence.Therefore,it is difficult to determine a proper model to reflect the dependence of social public governance score on many influencing factors by using the traditional parametric modeling method since a great number of factors affect the public governance scores in various ways.The regression tree algorithm has become one of the most popular algorithms in machine learning and data mining because of its high efficiency and easy implementation.It has the advantages of small computation,easy interpretation and little data preparation.The boosted regression tree greatly improves the prediction accuracy of the regression tree by combining a series of regression trees.As a nonparametric model,it has attracted much attention in the field of machine learning in recent years.It has high modeling efficiency,easy interpretation,as well as other advantages.In this paper,several years'data of 18 centers or municipalities in China,including Beijing,Shanghai,Tianjin,Chongqing,Hangzhou,Wuhan,Changsha,Xi'an and Inner Mongolia,have been collected.The other 10 variables are used as predictors,and the regression tree is used to explore the factors that have great influences on the social governance scores of urban social communities.The relative influences of different factors in the regression tree are compared with respect to the strength and their function forms.The conclusion of this paper is expected to provide a reference for the city to improve its public governance score,and to provide a better foundation for people's life.
Keywords/Search Tags:Social public governance score, Boosting, Regression tree, Factor analysis
PDF Full Text Request
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