Multi-selection of instances: A straightforward way to improve evolutionary instance selection

Although many more complex learning algorithms exist, k-nearest neighbor is still one of the most successful classifiers in real-world applications. One of the ways of scaling up the k-nearest neighbors classifier to deal with large datasets is instance selection. Due to the constantly growing amount of data in almost any pattern recognition task, we need more efficient instance selection algorithms, which must achieve larger reductions while maintaining the accuracy of the selected subset.