A Method for Entity Resolution in High Dimensional Data Using Ensemble Classifiers

Algorithm 2

Pseudocode of ensemble classifiers’ model.

Begin

 Initialize parameters and each base binary classifier’s Pareto archive

For each base binary classifier do

For each value do

 Search for the optimal solution (feature subset) by Algorithm 1 under current value (cardinality of features)

End for

 Update current base binary classifier’s archive based on analysis (ii) in Section 4.2

End for

 Choose a solution (feature subset) as the current base binary classifier’s input based on analysis (iii) in Section 4.2

 Apply max-wins voting method to aggregate classifiers

End