Discrimination Avoidance Methods in Data Mining

Abstract

Discrimination like privacy is a big issue when legal and ethical aspects of Data mining are considered. Most people don’t like to be discriminated for their gender, religion, nationality, age and so on, especially when those attributes are needed for making decisions. Decisions like giving them a job, loan, insurance, etc. Hence it is highly desirable to discover such potential biases and eliminating them from the training data without harming their decision-making utility .Therefore antidiscrimination techniques including discrimination discovery and prevention have been introduced in data mining. Discrimination prevention consist inducing patterns which do not lead to discriminatory decisions even if the original training datasets are inherently biased. So By focusing on the discrimination prevention, we present a group of pre-processing discrimination prevention methods with different features of each approach and how These approaches deal with direct or indirect discrimination.

Authors and Affiliations

Prajakta A. Soundankar

Keywords

Related Articles

A Stacked Ensemble Framework for Detecting Malicious Insiders

One of the mainstream strategies identified for detecting Malicious Insider Threat (MIT) is building stacking ensemble Machine Learning (ML) models to reveal malevolent insider activities through anomalies in user activi...

Precision Irrigation in Agriculture Using an IoT Based Smart Water Management Platform: A Review Paper

Water is available for something like the world's public's energy security, with agribusiness accounted for 70% of river use. Leaks in transit and land management, while also suitable processing practices, are the leadin...

Techniques for Data Mining Prediction in the Health Care Sector

Data mining is another term for knowledge discovery in databases (KDD). It's an interdisciplinary field that focuses on rooting meaningful knowledge from data in all sectors similar as health, education, and business. Cu...

CMRepo End-to-End Automation

Performance Automation is a technique which helps in determining the performance of the system, by determining various system parameters under different workloads. This project aims at developing the framework for determ...

A Review on Increasing Soil Carbon Storage: Mechanisms, Effects of Agricultural Practices and Proxies

The worldwide 4 per 1000 project seeks to assist governments and non-governmental organizations in their efforts to improve soil carbon (C) stock management. These stocks are depending on soil C emissions and inputs. The...

Download PDF file
  • EP ID EP748987
  • DOI -
  • Views 49
  • Downloads 0

How To Cite

Prajakta A. Soundankar (2015). Discrimination Avoidance Methods in Data Mining. International Journal of Innovative Research in Computer Science and Technology, 3(1), -. https://europub.co.uk/articles/-A-748987