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首页 » AI-NN-PR » 基于自组织特征映射网络的聚类分析,是在神经网络基础上发展起来的一种新的非监督聚类方法,分析了基于自 组织特征映射网络聚类的学习过程,分析了权系数自组织过程中...

基于自组织特征映射网络的聚类分析,是在神经网络基础上发展起来的一种新的非监督聚类方法,分析了基于自 组织特征映射网络聚类的学习过程,分析了权系数自组织过程中...

于 2022-04-18 发布 文件大小:35.54 kB
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基于自组织特征映射网络的聚类分析,是在神经网络基础上发展起来的一种新的非监督聚类方法,分析了基于自 组织特征映射网络聚类的学习过程,分析了权系数自组织过程中邻域函数和学习步长的一般取值问题,给出了基于自组织 特征映射网络聚类实现的具体算法,并通过实际示例测试,证实了算法的正确性。 -Based on self-organizing feature map network cluster analysis, neural network is developed on the basis of a new non-supervised clustering method, analysis based on self-organizing feature map network clustering of the learning process, analyzed the weights of self-organization the process of neighborhood function and learning step-size problem of the general values are given based on the self-organizing feature map network clustering algorithm to achieve concrete and practical examples of tests, confirmed the correctness of the algorithm.

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