A Hybrid Online Sequential Extreme Learning Machine with Simplified Hidden Network
نویسنده
چکیده
In this paper, a novel learning algorithm termed Hybrid Online Sequential Extreme Learning Machine (HOSELM) is proposed. The proposed HOS-ELM algorithm is a fusion of the Online Sequential Extreme Learning Machine (OS-ELM) and the Minimal Resource Allocation Network (MRAN). It is capable of reducing the number of hidden nodes in Single-hidden Layer Feed-forward Neural Networks (SLFNs) with Radial Basis Function (RBF) by virtue of adjustment in node allocation and pruning capability. Simulation results show that the generalization performance of the proposed HOS-ELM is comparable to the original OSELM with significant reduction in the number of hidden nodes.
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