An Approach to Reduce the Computational Burden of Nearest Neighbor Classifier
R. Raja Kumar, P. Viswanath, Chigarapalle Shoba Bindu · Procedia Computer Science · 2016
Nearest Neighbor Classifiers demand high computational resources i.e, time and memory. Reducing of reference set(training set) and feature selection are two different approaches to this problem. This paper presents a method to reduce the training set both in cardinality and dimensionality in cascade. The experiments are done on several bench mark datasets and the results obtained are satisfactory.