An exploration of algorithmic discrimination in data and classification
Computers and Society
2018-11-08 v1 Machine Learning
Abstract
Algorithmic discrimination is an important aspect when data is used for predictive purposes. This paper analyzes the relationships between discrimination and classification, data set partitioning, and decision models, as well as correlation. The paper uses real world data sets to demonstrate the existence of discrimination and the independence between the discrimination of data sets and the discrimination of classification models.
Cite
@article{arxiv.1811.02994,
title = {An exploration of algorithmic discrimination in data and classification},
author = {Jixue Liu and Jiuyong Li and Feiyue Ye and Lin Liu and Thuc Duy Le and Ping Xiong},
journal= {arXiv preprint arXiv:1811.02994},
year = {2018}
}
Comments
arXiv admin note: text overlap with arXiv:1811.01480