Globality-Locality Preserving Maximum Variance Extreme Learning Machine

Algorithm 1

GLELM algorithm.

Input: Initialize the training sample set ,

activation function , the number of hidden layer nodes is , the regularization

parameters are and ;

Output: Output weight matrix ;

Step 1: Randomly specify the network input weight and offset value , ;

Step 2: Calculate the hidden layer node output matrix by the activation function ;

Step 3: Calculate the manifold regularization framework according to formula (15) ;

Step 4: Calculate the output weight matrix from equation (20) .