Working with Self Organizing Maps - How do I interpret the results?
使用自组织映射——我如何解释这些结果？
Common approaches to unsupervised learning include k-Means, hierarchical clustering, and self-organizing maps.
无监管学习的常见方法包括k - Means、分层集群和自组织地图。
A method that applies the clustering function of SOFM (Self-Organizing Feature Maps) network is proposed for autonomous star pattern recognition.
介绍了一种利用自组织特征映射(SOFM)网络的聚类功能进行全天星图识别的方法。
An autonomous star pattern recognition method using the tri-star clustering function of SOFM (Self-Organizing Feature Maps) network is described.
介绍了一种利用SOFM(自组织特征映射)网络的聚类功能进行全天星图识别的算法。
Introducing diffusing and growing self-organizing maps (DGSOM), we propose a new algorithm called self-organized LLE and give some theoretical analysis.
引入扩散生长型自组织神经网络模型（DGSOM）算法，在深入研究LLE的基础上提出了新的自组织LLE算法并给出理论分析。
To facilitate clustering analysis and visualization of data, the Emergent Self-Organizing Feature Maps (ESOM) and a boundless U-matrix are needed.
本文通过利用涌现自组织特征映射神经网络对数据进行聚类分析，并通过无边界u矩阵实现可视化功能。
It implements two original algorithms specifically designed for clustering short time series together with hierarchical clustering and self-organizing maps.
它实现了两个专为短的时间序列聚类与聚类和自组织映射的原始算法。
It implements two original algorithms specifically designed for clustering short time series together with hierarchical clustering and self-organizing maps.
它实现了两个专为短的时间序列聚类与聚类和自组织映射的原始算法。
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