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基于监督式编码分类架构的自适应超限学习机

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摘要 针对传统超限学习(ELM)存在隐含层神经元数量大导致存储要求高和训练时间长的问题,提出了一种自适应接受域超限学习机模型(RF-A-ELM)。该模型通过建立一个深度超限学习网络作为监督自动编码的模块,即实现了训练模块。此外,在具有相同隐藏单元总数的条件下较传统ELM方法,该方法提供的快速训练算法极大的降低了训练时间。
出处 《电脑编程技巧与维护》 2019年第10期38-39,共2页 Computer Programming Skills & Maintenance
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