关于自组织映射(SOMs)和随机邻居嵌入(SNE)的统一观点

Artificial neural networks, ICANN : international conference ... proceedings. International Conference on Artificial Neural Networks (European Neural Network Society) Pub Date : 2022-05-03 DOI:10.48550/arXiv.2205.01492

Thibaut Kulak, Anthony Fillion, Franccois Blayo

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摘要

我们对两种广泛使用的数据可视化技术:自组织映射(SOMs)和随机邻居嵌入(SNE)提出了统一的观点。我们证明它们都可以从一个共同的数学框架中推导出来。利用这一公式，我们建议在两个数据集上定量地比较SOM和SNE，并讨论利用这两种方法的未来工作的可能途径。

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A unified view on Self-Organizing Maps (SOMs) and Stochastic Neighbor Embedding (SNE)

We propose a unified view on two widely used data visualization techniques: Self-Organizing Maps (SOMs) and Stochastic Neighbor Embedding (SNE). We show that they can both be derived from a common mathematical framework. Leveraging this formulation, we propose to compare SOM and SNE quantitatively on two datasets, and discuss possible avenues for future work to take advantage of both approaches.

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Artificial neural networks, ICANN : international conference ... proceedings. International Conference on Artificial Neural Networks (European Neural Network Society)

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