基于成對樣本比較的相對貧困識別特征正交篩選方法

打開文本圖片集

中圖分類號：0212.4 文獻(xiàn)標(biāo)志碼：A doi：10.12415/j.issn.1671-7872.24029

Orthogonal Feature Screening Method for Relative Poverty Identification Based on Pairwise Sample Comparison

CHANG Zhipeng'， CHEN Wenhe2，3

（1.School ofBusiness，Anhui UniversityofTechnology，Maanshan 243o32，China;2.SchoolofEconomicsand Management， Anhui Normal University，Wuhu 2410o，China; 3.Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes， Anhui University of Technology，Maanshan 243032， China）

Abstract：Toaddress the isse offeature selection forrelative poverty identification，anorthogonal selection method based on pairwise-sample comparison was proposed.Paired sample sets of“relative poverty”and“non-relative poverty”were collcted by means of pairwise by means of pairwise comparison. Then， a new feature subset evaluation function was designed based on the idea of puling similar samples closer and pushing dissimilar samples further apart.Finally，orthogonal experimental design was employed to select features.To validate the effectiveness of the method， 356 registered poor households and 212 non-registered poor households from the Dabie Mountain area were considered as esearch subjects.Four sets of paired sample sets were randomly constructed to screen four groups of keyfeatures，and seven classifiers includinglogisticregression，decision tree，support vectormachine，deep neural network，random forest，Boosting，and naive Bayes were tested for performance evaluation.The results indicate that，with the exception of the decision tree，accuracy，sensitivity，specificityand AUC values exceeding 90% are achieved by the other six classifiers across allfour sets of key features.Minimal variation is observed in the identification performance offeatures selected from diferent sample sets，and comparable performance to that of the fullfeatreset isattained byallfoursetsof keyfeatures.The proposed method ischaracterized byitssimple principle and operational convenience，making it suitable for scenarios where relative poverty clasification standards are lacking or dificult to establish，thereby enabling effective screening ofidentification features.

Keywords： relative poverty; key features; feature selection; paired comparison; orthogonal experiment; Mahalanobis distance; Dabie mountain area; identification

2020年我國脫貧攻堅戰(zhàn)取得全面勝利，歷史性地解決了絕對貧困問題。（剩余10160字）