Missing is useful: Missing values in cost-sensitive decision trees

IEEE Computer Soc
Publication Type:
Journal Article
IEEE Transactions On Knowledge And Data Engineering, 2005, 17 (12), pp. 1689 - 1693
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Many real-world data sets for machine learning and data mining contain missing values and much previous research regards it as a problem and attempts to impute missing values before training and testing. In this paper, we study this issue in cost-sensiti
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