Techniques for Dealing with Missing Values in Classification (1997)
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@MISC{White97techniquesfor,
author = {Liu White and W. Z. Liu and A. P. White and S. G. Thompson and M. A. Bramer},
title = {Techniques for Dealing with Missing Values in Classification},
year = {1997}
}
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Abstract
. A brief overview of the history of the development of decision tree induction algorithms is followed by a review of techniques for dealing with missing attribute values in the operation of these methods. The technique of dynamic path generation is described in the context of treebased classification methods. The waste of data which can result from casewise deletion of missing values in statistical algorithms is discussed and alternatives proposed. Keywords: Missing values, Dynamic path generation, Intelligent data analysis, Inductive learning, Knowledge discovery, Data mining, Machine learning. 1 Introduction In the information age, data is generated almost everywhere: satellites orbiting the moons of Jupiter; submarines in the deepest ocean trench; even electronic point of sale machines in the high street produce data. All of these systems generate millions of megabytes of data every day. Some of these data contain information that could lead to important discoveries in science; s...
