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Chi-Square and PCA Based Feature Selection for diabetes Detection with Ensemble Classifier

Intelligent Automation & Soft Computing 2023年第5期36卷 1931-1949页

作者： Vaibhav Rupapara Furqan Rustam Abid Ishaq Ernesto Lee Imran Ashraf School of Computing and Information Sciences Florida International UniversityUSA Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Computer Science Broward CollegeBroward CountyFloridaUSA Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

diabetes mellitus is a metabolic disease that is ranked among the top 10 causes of death by the world health *** the last few years,an alarming increase is observed worldwide with a 70%rise in the disease since 2000 and an 80%rise in male *** untreated,it results in complications of many vital organs of the human body which may lead to *** detection of diabetes is a task of signiﬁcant importance to start timely *** study introduces a methodology for the classiﬁcation of diabetic and normal people using an ensemble machine learning model and feature fusion of Chi-square and principal component *** ensemble model,logistic tree classiﬁer(LTC),is proposed which incorporates logistic regression and extra tree classiﬁer through a soft voting *** are also performed using several well-known machine learning algorithms to analyze their performance including logistic regression,extra tree classiﬁer,AdaBoost,Gaussian naive Bayes,decision tree,random forest,and k nearest *** addition,several experiments are carried out using principal component analysis(PCA)and Chi-square(Chi-2)fea-tures to analyze the inﬂuence of feature selection on the performance of machine learning classiﬁ*** indicate that Chi-2 features show high performance than both PCA features and original ***,the highest accuracy is obtained when the proposed ensemble model LTC is used with the proposed fea-ture fusion framework-work which achieves a 0.85 accuracy score which is the highest of the available approaches for diabetes *** addition,the statis-tical T-test proves the statistical signiﬁcance of the proposed approach over other approaches.

关键词： diabetes mellitus prediction feature fusion ensemble classiﬁer principal component analysis chi-square

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