Affiliation:
1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India
Abstract
Abstract
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 and streaming data. The results of these algorithms using MCNN and pMCNN have been compared with an existing algorithm for streaming data.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Hardware and Architecture,Modelling and Simulation,Information Systems
Reference18 articles.
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18 articles.
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