Natural neighborhood graph-based instance reduction algorithm without parameters.

•It proposes a natural neighborhood graph-based instance reduction algorithm.•It solves the parameter selection problem because the proposed algorithm does not need any parameters.•It significantly improves the reduction rate, while maintaining or even improving classification accuracy.•It can reduce the number of training set greatly, and the fluctuation of reduction rates is small for different kinds of datasets.