A Method of Discovering Tolerance Markov Blanket based on Completely Dependent Unknown Components
نویسندگان
چکیده
A novel tolerance feature subset selection method from incomplete data set, denoted by MaxGIIAMB, is proposed to pick out the Markov-boundary (MB), the minimal subset of features, of target variable but without making any assumption about the unknown component distribution. The classification experimental results of risk factors observed in a sample of 1841 employees of a Czech car factory demonstrate the practicability and superiority of our method over the classical expectation-maximization (EM) and available case technique (ACA).
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