A SURVEY ON DISCRIMINATION DETERRENCE IN DATA MINING

Arati Shrimant Mote, G. P. Chakote

Abstract: For extracting useful knowledge which is hidden in large set of data, Data mining is a very important technology. There are some negative perceptions about data mining. This perception may contain unfairly treating people who belongs to some specific group. Classification rule mining technique has covered the way for making automatic decisions like loan granting/denial and insurance premium computation etc. These are automated data collection and data mining techniques. According to discrimination attributes if training data sets are biases then discriminatory decisions may ensue. Thus in data mining antidiscrimination techniques with discrimination discovery and prevention are included. It can be direct or indirect. . When choices are created depending on delicate features that period the discrimination is oblique. The elegance is oblique when choices are created depending on nonsensitive features which are strongly correlated with one-sided delicate ones. The suggested system tries to deal with elegance protection in information exploration. It suggests new improved techniques applicable for immediate or oblique elegance protection independently or both simultaneously. Conversations about how to clean coaching information sets and contracted information places in such a way that immediate and/or oblique discriminatory decision guidelines are transformed to genuine classification guidelines are done. New analytics to evaluate the utility of the suggested methods are suggests and comparison of these methods is also done.

Keywords: Antidiscrimination, information exploration, oblique and immediate elegance protection, concept protection, concept generalization, privacy.

DOI: https://doi.org/10.15623/ijret.2015.0403024