  Data quality on categorical attribute is a difficult problem that has not
received as much attention as numerical counterpart. Our basic idea is to
employ association rule for the purpose of data quality measurement. Strong
rule generation is an important area of data mining. Association rule mining
problems can be considered as a multi objective problem rather than as a single
objective one. The main area of concentration was the rules generated by
association rule mining using genetic algorithm. The advantage of using genetic
algorithm is to discover high level prediction rules is that they perform a
global search and cope better with attribute interaction than the greedy rule
induction algorithm often used in data mining. Genetic algorithm based approach
utilizes the linkage between association rule and feature selection. In this
paper, we put forward a Multi objective genetic algorithm approach for data
quality on categorical attributes. The result shows that our approach is
outperformed by the objectives like accuracy, completeness, comprehensibility
and interestingness.
