Stream-Based Extreme Learning Machine Approach for Big Data Problems

Algorithm 1

Active Learning strategy.

Input: Initial size of the training set , maximum number of labels , ELM random weights and random bias , generator

function

Output: Weights vector

Method:

Take at random pattens from the generator function ;

Propagate the pattens through the ELM layer () and query its labels ;

;

;

;

Repeat

 Take at random a pattern from ;

;

 ;

;

 ;

 if    then

  Query the label ;

  Update  ;

  ;

 end

Until  () or (  =  ⌀);