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Parallel MCNN (pMCNN) with Application to Prototype Selection on Large and Streaming Data
2017
Journal of Artificial Intelligence and Soft Computing Research
The Modified Condensed Nearest Neighbour (MCNN) algorithm for prototype selection is order-independent, unlike the Condensed Nearest Neighbour (CNN) algorithm. Though MCNN gives better performance, the time requirement is much higher than for CNN. To mitigate this, we propose a distributed approach called Parallel MCNN (pMCNN) which cuts down the time drastically while maintaining good performance. We have proposed two incremental algorithms using MCNN to carry out prototype selection on large
doi:10.1515/jaiscr-2017-0011
fatcat:yrzysokhrnfqrhw4oayevpjyn4