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Showing 1 to 4 of 4 for “"subgroup discovery"”.

  1. Identifying, Measuring, and Addressing Algorithmic Bias in AI Admission Systems for Graduate Education

    … can lead to unfair outcomes for underprivileged subgroups among applicants. Recent changes in legislation such as the ban of affirmative action by the U.S. Supreme Court make it increasingly relevant to study the demographic composition of admitted students and ensure that we develop fair machine …

    vt Repository record for Identifying, Measuring, and Addressing Algorithmic Bias in AI Admission Systems for Graduate Education (opens in a new tab)

  2. OWL-Miner: Concept Induction in OWL Knowledge Bases

    … both classification (predictive induction) and subgroup discovery (descrip- tive induction), which, in this context, are fundamentally related. We have implemented our methods as the system called OWL-Miner and show by evaluation that our methods outperform state-of-the-art systems for DL …

    aus-cath Repository record for OWL-Miner: Concept Induction in OWL Knowledge Bases (opens in a new tab)

  3. OWL-Miner: Concept Induction in OWL Knowledge Bases

    … both classification (predictive induction) and subgroup discovery (descrip- tive induction), which, in this context, are fundamentally related. We have implemented our methods as the system called OWL-Miner and show by evaluation that our methods outperform state-of-the-art systems for DL …

    anu Repository record for OWL-Miner: Concept Induction in OWL Knowledge Bases (opens in a new tab)

  4. Discovering Group Differences from Qualitative and Quantitative Attributes Using Contrast Set Mining with Discretization and Measures of Interestingness

    … the mining step, the task to be performed is the discovery of valid contrast sets. A valid contrast set is a conjunction of attributes and values that differ meaningfully in their distribution across groups. We introduce a novel contrast set, called the λ-contrast set. A λ-contrast set has a ratio …

    regina Repository record for Discovering Group Differences from Qualitative and Quantitative Attributes Using Contrast Set Mining with Discretization and Measures of Interestingness (opens in a new tab)