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An Improved Local Coupled Extreme Learning Machine

机译:改进的本地耦合极限学习机

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Local Coupled Extreme Learning Machine (LCELM) is a recently-proposed variant of ELM, which assigns an address for each hidden-layer node and activates the hidden-layer node when its activated degree is less than a given threshold. In this paper, an improved version of LCELM is proposed by developing a new way to initialize the address for each hidden-layer node and calculating the activated degree of hidden-layer node with Gaussian kernel. The experimental comparison with ELM and LCELM demonstrates the feasibility and effectiveness of improve LCELM which obtains the higher testing accuracy without significantly increasing the training time of ELM.
机译:本地耦合极限学习机(LCELM)是ELM的最新提议,它为每个隐藏层节点分配一个地址,并在其激活程度小于给定阈值时激活该隐藏层节点。本文提出了一种改进的LCELM版本,该方法通过开发一种新方法来初始化每个隐藏层节点的地址并使用高斯核计算隐藏层节点的激活程度。与ELM和LCELM的实验比较证明了改进LCELM的可行性和有效性,它可以在不显着增加ELM训练时间的情况下获得更高的测试准确性。

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