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.
翻译:我们对两种广泛使用的数据可视化技术提出统一的看法:自制地图(SOMS)和实心邻里嵌入图(SNE),我们表明它们都可以从一个共同的数学框架衍生出来。 我们提议利用这一提法,在两个数据集上对SOM和SNE进行定量比较,并讨论未来工作利用这两种方法的可能途径。