Program Committee Members
2007 IEEE International Conference on Granular Computing (GRC 2007) · 2007
In this paper we consider incomplete data sets, i.e., data sets with missing attribute values. Two different types of missing attribute values are studied: lost and do not care. Furthermore, three definitions of approximations are discussed: singleton, subset, and concept. Theoretically, singleton approximations should not be used in data mining since concepts approximated by singleton approximations are not definable. However, we conducted a number of experiments on 44 different incomplete data sets using all three approximation definitions and our results show that none of these approximations is superior to the other.