mimic_preprocessed

<p>This version of the <code>mimic</code> dataset has been cleaned by removing columns with more than 10% missing data, imputing remaining missing values with the median, and dropping columns highly correlated with the outcome. It is designed for use in fairness-aware machine learning tasks and streamlined analysis.</p>

datasets

A collection of functions for computing fairness metrics for machine learning and statistical models, including confidence intervals for each metric. The package supports the evaluation of group-level fairness criterion commonly used in fairness research, particularly in healthcare. It is based on the overview of fairness in machine learning written by Gao et al (2024) <doi:10.48550/arXiv.2406.09307>.

Benjamin Smith

fairmetrics

Fairness Evaluation Metrics with Confidence Intervals

Jianhui Gao

Benson Chou

Jessica Gronsbell

mimic_preprocessed function

<p>A data frame with fewer variables than the original due to preprocessing. Number of rows: 1776.</p>

Format

Preprocessed Clinical Data from the MIMIC-II Database — mimic_preprocessed

Preprocessed Clinical Data from the MIMIC-II Database

mimic_preprocessed: Preprocessed Clinical Data from the MIMIC-II Database

Description

Usage

Arguments

Format

See Also