22 datasets found

The law school example dataset, used to test the fairness of algorithms.

The authors used two tabular datasets, Adult and Credit, that are ubiquitous in fairness literature, and transformed them into multi-label settings.

This paper describes a differentially private post-processing algorithm for learning attribute-aware fair regressors.

This paper describes a differentially private post-processing algorithm for learning attribute-aware fair regressors.

This paper describes a differentially private post-processing algorithm for learning attribute-aware fair regressors.

ACSEmployment is another one of the five pre-defined tasks in the Folktables dataset [17]. We use the same subset from the state of California, USA for 2018 as above. The...

ACSIncome is one of the five pre-defined tasks in the Folktables dataset [17], which was recently collected to improve the older and commonly used UCI Adult Income dataset [19]....

The training data often in obtained from social surveys. In social surveys, oftentimes the data collection process is a strata sampling, e.g. due to cost restrictions. In strata...

The dataset used in the paper is a set of UCI datasets, including adult, census, covertype, financial, joke, mushroom, and statlog.

The dataset used in this paper is the Crime dataset, which is a real-world UCI Machine Learning Census dataset for violent state prediction.

The proposed framework was tested on four datasets, three of which are commonly used benchmarks. Two datasets (German credit and Adult income) come from the UCI ML repository...

The ACS-Income dataset is a dataset used for evaluating the fairness of machine learning models. It contains information about individuals and their income.

The dataset used in the paper for fair subgroup mixup for improving group fairness.

The dataset used in the paper for fair subgroup mixup for improving group fairness.

The COMPAS recidivism dataset contains 6,167 samples, and the task is to predict the recidivism of an individual based on criminal history, with the binary protected attribute...

The Bank Marketing dataset is a commonly used dataset in the fairness literature, containing information about individuals' demographic and economic characteristics.

The dataset used in this paper is the German dataset, which is a real-world UCI Machine Learning dataset extracted from a German bank for default prediction.

A commonly observed pattern in machine learning models is an underprediction of the target feature, with the model’s predicted target rate for members of a given category...

The dataset used in this paper is not explicitly described, but it is mentioned that it contains four DAGs representing well-known exposure-outcome relationships in the medical...

The dataset comprises of phone call records of a marketing campaign run by a Portuguese bank. The marital status of the clients is considered feature to ensure fairness.