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- W2386792210 abstract "To solve the problem of incorrect parent,child,and spouse nodes being brought into the current algorithms,an improved algorithm called a regression analysis-max min Markov blanket(RA-MMMB) was presented using the Markov Blanket based on logistic regression analysis.First,a logistic regression equation was established between the target variable and a set of its candidate Markov blankets obtained from the max-min Markov blanket(MMMB) algorithm.Regression analysis can retain the variables strongly correlated with the target variable,and can remove the error variables and other variables weakly correlated with it as well.The incorrect nodes in the MMMB algorithm were also removed from the candidate Markov blanket;then,after the G2 conditiond independence test,which removed the brother node of the target variable in the candidate Markov blanket,returned after the regression analysis,the Markov blanket of the target variable was obtained.By the method of regression analysis,the RA-MMMB algorithm reduces the number of condition tests of independence and improves the accuracy of discovering the Markov blanket for the target variable.The result shows that the method can discover the Markov blanket of the target variable efficiently." @default.
- W2386792210 created "2016-06-24" @default.
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- W2386792210 date "2012-01-01" @default.
- W2386792210 modified "2023-09-26" @default.
- W2386792210 title "An algorithm for a Markov blanket based on logistic regression analysis" @default.
- W2386792210 hasPublicationYear "2012" @default.
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