Abstract
This paper extends the rough set approach for JEP induction based on the notion of a condensed decision table. The original transaction database is transformed to a relational form and patterns are induced by means of local reducts. The transformation employs an item aggregation obtained by coloring a graph that re0ects con0icts among items. For e±ciency reasons we propose to perform this preprocessing locally, i.e. at the transaction level, to achieve a higher dimensionality gain. Special maintenance strategy is also used to avoid graph rebuilds. Both global and local approach have been tested and discussed for dense and synthetically generated sparse datasets.
The research has been partially supported by grant No 3 T11C 002 29 received from Polish Ministry of Education and Science.
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Terlecki, P., Walczak, K. (2007). Local Table Condensation in Rough Set Approach for Jumping Emerging Pattern Induction. In: Akhgar, B. (eds) ICCS 2007. Springer, London. https://doi.org/10.1007/978-1-84628-992-7_14
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DOI: https://doi.org/10.1007/978-1-84628-992-7_14
Publisher Name: Springer, London
Print ISBN: 978-1-84628-990-3
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