Alice and the Caterpillar: A more descriptive null model for assessing data mining results
Giulia Preti,
Gianmarco De Francisci Morales,
Matteo Riondato
Abstract:We introduce novel null models for assessing the results obtained from observed binary transactional or sequence datasets, using statistical hypothesis testing. Our null models maintain more properties of the observed dataset than existing ones. Specifically, they preserve the Bipartite Joint Degree Matrix of the bipartite (multi-)graph corresponding to the dataset, which ensures that the number of caterpillars, i.e., paths of length three, is preserved, in addition to other properties considered by other mode… Show more
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