RMSE-ELM: Recursive Model Based Selective Ensemble of Extreme Learning Machines for Robustness Improvement

Algorithm 2

RMSE-ELM.

Given: training set , (the size of ensemble groups in the first layer), (the size

                  of each ensemble in the first layer), (the size of candidates pool in the second

                  layer), is defined in (7), threshold is a pre-set value (reciprocal value of or ).

Steps:

(1) for

                  { ;

                           for 

                           { Training each ELM network;

                                     Generating a population of weight vector;

                                     Using selective ensample to get the best weight vector ;

                                     Removing base ELMs that the weights less than ;

                          }

                                     Calculating the whole remained ELMs of group are ;

            ;

                  }

(2) Training remained ELM;

(3) Using selective ensemble to get the best weight vector ;

(4) Removing base ELMs that the weights less than ;

(5) Getting the final prediction;