Prototype reduction based on Direct Weighted Pruning
A novel method to condense databases for any instance-based learning algorithm. It directly models the two objectives of data condensation & classification accuracy. Very simple training/optimization procedure with evolutionary search. Its training uses 3 novel acceleration heuristics to notably speed up convergence. Comparisons with too many datasets and multiple state-of-the-art algorithms.
prototype reduction data condensation instance weight learning