C4.5: programs for machine learning
C4.5: programs for machine learning
Data mining for discrimination discovery
ACM Transactions on Knowledge Discovery from Data (TKDD)
DCUBE: discrimination discovery in databases
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Three naive Bayes approaches for discrimination-free classification
Data Mining and Knowledge Discovery
Fairness-Aware classifier with prejudice remover regularizer
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Discrimination discovery in scientific project evaluation: A case study
Expert Systems with Applications: An International Journal
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With the support of the legally-grounded methodology of situation testing, we tackle the problems of discrimination discovery and prevention from a dataset of historical decisions by adopting a variant of k-NN classification. A tuple is labeled as discriminated if we can observe a significant difference of treatment among its neighbors belonging to a protected-by-law group and its neighbors not belonging to it. Discrimination discovery boils down to extracting a classification model from the labeled tuples. Discrimination prevention is tackled by changing the decision value for tuples labeled as discriminated before training a classifier. The approach of this paper overcomes legal weaknesses and technical limitations of existing proposals.