Random Search Enhancement of Error Minimized Extreme Learning Machine
Yuan Lan, Yeng Chai Soh, Guang-Bin Huang · 2010
Abstract. Error Minimized Extreme Learning Machine (EM-ELM) proposed by Feng et al. [1] can automatically determine the number of hidden nodes in generalized Single-hidden Layer Feedforward Networks (SLFNs). We recently found that some of the hidden nodes that are added into the network may play a very minor role in the network output, which increases the network complexity. Hence, this paper proposes an Enhancement of EM-ELM (referred to as EEM-ELM), which introduce a selection phase based on the random search method. The empirical study shows that EEM-ELM leads to a more compact network structure. 1