33 citations · 79 across the 35 of their papers we have counts for
24 papers · 1 filter
A Comparative Study of Discretization Approaches for Granular Association Rule Mining
Xu He, Fan Min, William Zhu
Granular association rule mining is a new relational data mining approach to reveal patterns hidden in multiple tables. The current research of granular association rule mining con…
Cost-Sensitive Feature Selection of Data with Errors
Hong Zhao, Fan Min, William Zhu
In data mining applications, feature selection is an essential process since it reduces a model's complexity. The cost of obtaining the feature values must be taken into considerat…
Cost-sensitive C4.5 with post-pruning and competition
Zilong Xu, Fan Min, William Zhu
Decision tree is an effective classification approach in data mining and machine learning. In applications, test costs and misclassification costs should be considered while induci…
Minimal cost feature selection of data with normal distribution measurement errors
Hong Zhao, Fan Min, William Zhu
Minimal cost feature selection is devoted to obtain a trade-off between test costs and misclassification costs. This issue has been addressed recently on nominal data. In this pape…
Matrix approach to rough sets through vector matroids over a field
Aiping Huang, William Zhu
Rough sets were proposed to deal with the vagueness and incompleteness of knowledge in information systems. There are may optimization issues in this field such as attribute reduct…
Characteristic of partition-circuit matroid through approximation number
Yanfang Liu, William Zhu
Rough set theory is a useful tool to deal with uncertain, granular and incomplete knowledge in information systems. And it is based on equivalence relations or partitions. Matroid…