Quantitative Association Rules
Recently, the problem of including numerical parameters in patterns and association rules attracted some interest in data mining. Taking into account numbers in pattern mining, the definition of patterns and rules becomes a non-trivial problem. We present a new approach to quantitative association rules based on half-spaces and show how it can be applied to the problem of gene expression data analysis (see below). An implementation of the tool is provided online under the GNU GPL.
Publications
Rückert, U, Richter, L, and Kramer, S
(2004).
Quantitative Association Rules Based on Half-Spaces: An Optimization Approach
In: Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM-2004), vol. 00, pp. 507-510, Los Alamitos, CA, USA, IEEE Computer Society Press.
Rückert, U, Richter, L, and Kramer, S
(2004).
Quantitative Association Rules Based on Half-Spaces
Technische Universität München, München.
Georgii, E, Richter, L, Rückert, U, and Kramer, S
(2005).
Analyzing Microarray Data Using Quantitative Association Rules
Bioinformatics, 21(2):ii1-ii8.
Software
Download MATLAB Source Code: qar
Please cite [RRK04a] if you are using the software in a publication.