IPRed: Instance Reduction Algorithm Based on the Percentile of the Partitions.

Instance reduction methods are popular methods that reduce the size of the datasets to possibly improve the classification accuracy. We present a method that reduces the size of the dataset based on the percentile of the dataset partitions which we call IPRed. We evaluate our and other popular instance reduction methods from a classification perspective by 1-nearest neighbor algorithm on many real datasets. Our experimental evaluation on the datasets shows that our method yields the minimum average error with statistical significance.