In this paper we examine the effect that the choice of support and confidence thresholds has on the accuracy of classifiers obtained by Classification Association Rule Mining. ...
Associative classification is a promising classification approach that utilises association rule mining to construct accurate classification models. In this paper, we investigate ...
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
Abstract. We present a simple Data Mining Logic (DML) that can express common data mining tasks, like “Find Boolean association rules” or “Find inclusion dependencies.” At ...
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...