tsnedistill

由MWattenberg著作·2016·被引用812次—Apopularmethodforexploringhigh-dimensionaldataissomethingcalledt-SNE,introducedbyvanderMaatenandHintonin2008[1].,Althoughextremelyusefulforvisualizinghigh-dimensionaldata,t-SNEplotscansometimesbemysteriousormisleading.Sept8,2016.AttentionandAugmented ...,Forfurtherdetails,“HowtoUset-SNEEffectively”https://distill.pub/2016/misread-tsne/providesagooddiscussiono...

參考資訊如下
How to Use t-SNE Effectively

由 M Wattenberg 著作 · 2016 · 被引用 812 次 — A popular method for exploring high-dimensional data is something called t-SNE, introduced by van der Maaten and Hinton in 2008 [1] .

Distill — Latest articles about machine learning

Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading. Sept 8, 2016. Attention and Augmented ...

t-SNE

For further details, “How to Use t-SNE Effectively” https://distill.pub/2016/misread-tsne/ provides a good discussion of the effects of various parameters ...

t

更多细节， “如何有效地使用t-SNE” https://distill.pub/2016/misread-tsne/提供了一个很好的关于各种参数的影响的讨论，以及互动的情节。 circles, perplexity=5 in ...

t

A popular method for exploring high-dimensional data is something called t-SNE.This article explains what t-SNE is and how to use it effectively. Although ...

distillpubpost--misread-tsne: How to Use t

The content of this Distill article is licensed as CC-BY 4.0. Code is released under the Apache 2.0 License, even if enclosed inside a notebook or served as ...

默默地學Deep Learning (5)-如何有效地使用t

2018年6月21日 — ... t-SNE, introduced by van der Maaten and Hinton… distill.pub. 裡面有很多有趣的互動式體驗，強烈建議先到該網站去玩一下，會對於t-SNE有更深刻的了解。

t

2020年4月13日 — An intuitive explanation of t-SNE algorithm and why it's so useful in practice.

資料降維與視覺化：t

2019年6月4日 — t-SNE（t-distributed stochastic neighbor embedding，t-隨機鄰近嵌入法）是一種非線性的機器學習降維方法，由Laurens van der Maaten 和Geoffrey Hinton ...

Distill阅读How to Use t

2023年5月17日 — t-SNE算法适应“距离”的概念适应数据集中的区域密度变化。结果它自然地扩大了密集的集群，收缩了系数的集群，平衡了集群的大小。需要明确的是，这与任何降 ...