Abstract
Current approaches to market basket simulation neglect the fact that empty transactions are typically not recorded and therefore should not occur in simulated data. This paper suggest how the simulation framework without associations can be extended to avoid empty transactions and explores the possible consequences for several measures of interestingness used in association rule filtering.
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Buchta, C. (2007). Improving the Probabilistic Modeling of Market Basket Data. In: Decker, R., Lenz, H.J. (eds) Advances in Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70981-7_47
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DOI: https://doi.org/10.1007/978-3-540-70981-7_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70980-0
Online ISBN: 978-3-540-70981-7
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