Building selective ensembles of Randomization Based Neural Networks with the successive projections algorithm.

•We propose a selective ensemble method for Randomization Based Neural Networks (RNNs) based on the Successive Projections Algorithm (SPA).•The proposed method, named SERS, uses SPA for feature selection, neuron pruning and ensemble selection.•SERS was used to build three ensemble models based on Extreme Learning Machines, Feedforward Neural Network with Random Weights and Random Vector Functional Link networks.•The proposed methods result in compact models with performance comparable to other state-of-the-art RNN based methods.•Results showed that none of the previously proposed methods was able to achieve better results in both accuracy and model reduction.