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Extreme Learning Machine is a fast single layer feed forward neural network for real valued classification. It suffers from the problem of instability and over fitting. Voting based Extreme Learning Machine, VELM reduces this performance variation in Extreme Learning Machine by employing majority voting based ensembling technique. VELM improves the performance of ELM at the cost of increased redundancy. This problem can be reduced using ensemble pruning techniques. This work proposes and evaluates Voting based Extreme Learning Machine with Accuracy based ensemble Pruning, VELM_AP. VELM_AP generates component classifier in the same way as VELM. General Terms Real valued classification

Voting based Extreme Learning Machine with Accuracy based Ensemble Pruning