HIGHLIGHTS
- who: Leonardo Alexandre and collaborators from the Editor:, Hanyang University have published the research work: DISA tool: Discriminative and informative subspace assessment with categorical and numerical outcomes, in the Journal: PLOS ONE of 16/03/2022
- what: To address these limitations, this work proposes a methodology to rigorously assess association rules with expressive patterns in the antecedent and numerical outcomes in the consequent, thus avoiding the discovery of spurious association rules (false positives). Ergo, the authors propose DISA (Discriminative and Informative Subspace Analysis), a software package in Python to assess patterns with numerical outputs by . . .
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