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An experimental investigation on selection of a reference set for the k-Nearest Neighbors (k-NN) classification method has been conducted. Genetic algorithms have been employed bringing together the strategy to preserve the decision boundary and that of selecting the most ”typical” objects as prototypes. The chromosome is directly mapped onto the reference set and the best subset is subsequently evolved...
In a previous paper the use of GAs as an editing technique for the k-nearest neighbor (k-NN) classification technique has been suggested. Here we are looking at different fitness functions. An experimental study with the IRIS data set and with a medical data set has been carried out. Best results (smallest subsets with highest test classification accuracy) have been obtained by including in the fitness...
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