Weighted extreme learning machine for balance and optimization learning
Xiaojuan Ban, Ruoyi Liu, Qing Shen, Yu Wang · 2016
Extreme learning machine (ELM) is a simple and effective method of single-hidden layer feedforward neural network. On this basis, there are many other methods are proposed to improve ELM. Weighted extreme learning machine is one of those methods. Weighted ELM is simple in theory and convenient in implementation and it can be applied directly into multiclass classification tasks. This paper improves previous weighted ELM for balance and optimization learning. From the experimental results, the improved weighted ELM obtains the better effects in solving the multiclass classification tasks.