ISSN (Online) : 2456 - 0774

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ISSN (Online) 2456 - 0774



Abstract- Data mining is a technology using which we can
extract useful information from data. There are two major
issues in data mining first is privacy violation and second is
discrimination. Discrimination is the unfair treatment with
respect to the features that should not be considered while
decision making. With respect to human, it is when people
are given unfair treatment on the basis of their sensitive
features like gender, race, religion etc. Discrimination can
be of two types direct discrimination and indirect
discrimination. Direct discrimination consists of training
rules based on sensitive attributes like religion, race,
community etc. Indirect discrimination is a discrimination
which occurs when the decisions are taken on non-sensitive
attributes but these attributes are closely related to direct
discriminatory attributes. Automated decision making
systems uses data mining techniques to train the system for
decision making. Data form the previous work is used for
the rule generation to train the system. At first sight, we
can say that automating decisions systems are fair in
decision making, but if the training data sets are itself
discriminatory then the system cannot be free from
discrimination. To remove such discrimination we have
discrimination discovery and prevention techniques in data
mining. This paper mainly focuses direct discrimination
removal from the data.
Keywords –Data Mining, Direct Discrimination, Data Preprocessing,
Discrimination Prevention, Rule Protection, Rule

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