Research Article
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 |
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