Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data

Abstract

Discriminative patterns can provide valuable insights into data sets with class labels, that may not be available from the individual features or the predictive models built using them. Most existing approaches work efficiently for sparse or low-dimensional data sets. However, for dense and high-dimensional data sets, they have to use high thresholds to… (More)
DOI: 10.1109/TKDE.2010.241

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