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Extreme-Learning-Machine method

一、基本**:极限学习机(Extreme Learning Machine,ELM)由Guang-Bin Huang等[1]提出的用于求解单隐层神经网络的算法。

二、特点: (1)输入权重和隐含层偏置均随机产生,且设定后可不再调整; (2)隐含层和输出层之间的连接权值不需要迭代,通过解方程式一次性产生。 基于以上特点,ELM对于传统的神经网络,尤其是单隐层前馈神经网络(SLFNs),在保证学习精度的前提下比传统的学习算法速度更快。

Reference: [1]Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew. Extreme learning machine: Theory and applications[J]. Neurocomputing, 70(1-3):489-501.

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