On-Line Sequential Extreme Learning Machine

Guang-Bin Huang, Nanying Liang, Hai-Jun Rong, P. Saratchandran, N. Sundararajan · Computational intelligence · 2005

The primitive Extreme Learning Machine (ELM) [1, 2, 3] with additive neurons and RBF kernels was implemented in batch mode. In this paper, its sequential modification based on recursive least-squares (RLS) algorithm, which referred as Online Sequential Extreme Learning Machine (OS-ELM), is introduced. Based on OS-ELM, Online Sequential Fuzzy Extreme Learning Machine (Fuzzy-ELM) is also introduced to implement zero order TSK model and first order TSK model. The performance of OS-ELM and Fuzzy-ELM are evaluated and compared with other popular sequential learning algorithms, and experimental results on some real benchmark regression problems show that the proposedOnlineSequentialExtreme Learning Machine (OS-ELM) produces better generalization performance at very fast learning speed.

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