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Krimp: mining itemsets that compress
Open accessAbstract
One of the major problems in pattern mining is the explosion of the number of results. Tight constraints reveal only common knowledge, while loose constraints lead to an explosion in the number of returned patterns. This is caused by large groups of patterns essentially describing the same set of transactions. In this paper we approach this problem using the MDL principle: the best set of patterns is that set that compresses the database best. For this task we introduce the Krimp algorithm. Experimental evaluation shows that typically only hundreds of itemsets are returned; a dramatic reduction, up to seven orders of magnitude, in the number of frequent item sets. These selections, called code tables, are of high quality. This is shown with compression ratios, swap-randomisation, and the accuracies of the code table-based Krimp classifier, all obtained on a wide range of datasets. Further, we extensively evaluate the heuristic choices made in the design of the algorithm.
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Elements of Information Theory
Cover, T. M., & Thomas, J. A. (2001) · Wiley eBooks · doi:10.1002/0471200611 · Cited by 36,808
Data Mining: Practical Machine Learning Tools and Techniques
(2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,437
(1992) · Cited by 23,431
(1973) · CERN Document Server (European Organization for Nuclear Research) · Cited by 12,895
Reducibility among Combinatorial Problems
Karp, R. M. (1972) · Complexity of Computer Computations · doi:10.1007/978-1-4684-2001-2_9 · Cited by 11,511
Witten, I. H. (2008) · Cited by 9,143
Modeling by shortest data description
Rissanen, J. (1978) · Automatica · doi:10.1016/0005-1098(78)90005-5 · Cited by 6,011
An Introduction to Kolmogorov Complexity and Its Applications
Li, M., & Vitányi, P. (2019) · Texts in Computer Science · doi:10.1007/978-3-030-11298-1 · Cited by 3,681
Pattern Classification and Scene Analysis.
Clarke, M. R. B., Duda, R. O., & Hart, P. E. (1974) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344977 · Cited by 3,222
Fast discovery of association rules
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H. T. T., & Verkamo, A. I. (1996) · Knowledge Discovery and Data Mining · Cited by 2,376
Metadata
- Authors
- Vreeken, J., van Leeuwen, M., & Siebes, A.
- Venue
- Data Mining and Knowledge Discovery
- Published
- 2010-10-16
- Volume
- 23
- Issue
- 1
- Pages
- 169-214
- ISSN
- 1384-5810 (ISSN-L)
- 1573-756X
- OpenAlex
- W2124066753
- Cited by
- 300
- References
- 61
- FWCI
- 49.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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