Abstract. Association rule mining algorithms such as Apriori were originally developed to automatically detect patterns in sales transactions and were later on also successfully ap...
Effective information systems require the existence of explicit process models. A completely specified process design needs to be developed in order to enact a given business proce...
Laura Maruster, A. J. M. M. Weijters, Wil M. P. va...
While recent research on rule learning has focussed largely on finding highly accurate hypotheses, we evaluate the degree to which these hypotheses are also simple, that is small....
This draft paper describes a solution to the rule maintenance problem for data descriptor rules derived from data that may subsequently change. The method utilises any available c...
Jerome Robinson, Barry G. T. Lowden, Mohammed Al H...
Decision lists (or ordered rule sets) have two attractive properties compared to unordered rule sets: they require a simpler classification procedure and they allow for a more co...
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
A cascade model is a rule induction methodology using levelwise expansion of an itemset lattice, where the explanatory power of a rule set and its constituent rules are quantitativ...
Model trees—decision trees with linear models at the leaf nodes—have recently emerged as an accurate method for numeric prediction that produces understandable models. However,...
Experiments were carried out to investigate the possibility of training cellular automata to to perform processing. Currently, only binary images are considered, but the space of r...
At the International Research and Educational Institute for Integrated Medical Sciences (IREIIMS) project, we are collecting complete medical data sets to determine relationships b...