main webpage W Topic Data Mining arXiv (Cornell University) Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features 2023 The vast majority of techniques to train fair models require access to the protected attribute (e.g., race, gender), either at train time or in production. However, in many important applications this protected attribute is largely unavailable. In this paper,… Article Open Data Mining Open Article Page

Data Mining

Process of extracting and discovering patterns in large data sets Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Critical Symbolic Virtual Narrative Open Data Mining Open Article Page

Exploring foci of: arXiv (Cornell University) Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features 2023 The vast majority of techniques to train fair models require access to the protected attribute (e.g., race, gender), either at train time or in production. However, in many important applications this protected attribute is largely unavailable. In this paper, we develop methods for measuring and reducing fairness violations in a setting with limited access to protected attribute labels. Specifically, we assume access to protected attribute labels on a small subset of the dataset of interest, but only probabilistic… Open Article Page

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Explore Data Mining W Topic Data Mining arXiv (Cornell University) Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features 2023 The vast majority of techniques to train fair models require access to the protected attribute (e.g., race, gender), either at train time or in production. However, in many important applications this protected attribute is largely unavailable. In this paper,… Article Critical Symbolic Virtual Narrative Open Data Mining Open Article Page