Whenever a dataset has multiple discrete target variables, we want our algorithms to consider not only the variables themselves, but also the interdependencies between them. We pro...
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, M...
Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applicatio...
Yan Xing, Michael G. Madden, Jim Duggan, Gerard Ly...
In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...
Decision support systems are important in leveraging information present in data warehouses in businesses like banking, insurance, retail and health-care among many others. The mu...
In this paper, we present a framework for categorical data analysis which allows such data sets to be explored using a rich set of techniques that are only applicable to continuou...