This paper proposes an experimental evaluation of various discretization schemes in three different evolutionary systems for inductive concept learning. The various discretization...
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Exploring the vast number of possible feature interactions in domains such as gene expression microarray data is an onerous task. We describe Backward-Chaining Rule Induction (BCR...
Douglas H. Fisher, Mary E. Edgerton, Zhihua Chen, ...
Inclusion of domain knowledge in a process of knowledge discovery in databases is a complex but very important part of successful knowledge discovery solutions. In real-life data m...