Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
The goal of this paper is to develop methods to handle inconsistent knowledge elicited from multiple sources. Knowledge is represented using predicates that define relationships w...
Local pattern discovery, pattern set formation and global modeling may be viewed as three consecutive steps in a global modeling process. As each of these three steps have gained a...
We examine the notion of "unrelatedness" in a probabilistic framework. Three formulations are presented. In the first formulation, two variables a and b are totally inde...