[2002.05687] Tree-SNE: Hierarchical Clustering and Visualization Using t-SNEcontact arXivarXiv Twitter

t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology. Building on recent advances in speeding up t-SNE and obtaining finer-grained structure, we combine the two to create tree-SNE, a hierarchical clustering and visualization algorithm based on stacked one-dimensional t-SNE embeddings. We also introduce alpha-clustering, which recommends the optimal cluster assignment, without foreknowledge of the number of clusters, based off of the cluster stability across multiple scales. We demonstrate the effectiveness of tree-SNE and alpha-clustering on images of handwritten digits, mass cytometry (CyTOF) data from blood cells, and single-cell RNA-sequencing (scRNA-seq) data from retinal cells. Furthermore, to demonstrate the validity of the visualization, we use alpha-clustering to obtain unsupervised clustering results competitive with the state of the art on several image data sets. Software is available at https://github.com/isaacrob/trees

6 mentions: @upura0@AkiraTOSEI@GCLinderman@AkiraTOSEI@lpachter@lpachter
Keywords: clustering
Date: 2020/02/19 11:20

Referring Tweets

@AkiraTOSEI t.co/GgJjTi8KwB 階層的なクラスタリングができるTree-SNEを提案。 1次元に次元削減するt-SNEをperplexityとt分布の自由度aαを減少させながら、縦に並べることで実現する。 t.co/bdPX8TLufc
@GCLinderman We previously showed that varying the "degrees of freedom" of the t-SNE kernel resolves finer vs. coarser structure. The authors of tree-SNE use this idea with 1D t-SNE to do hierarchical clustering. Pretty interesting, and the figures are beautiful! t.co/gf1DAQOHhc t.co/D4neXW2VbR
@AkiraTOSEI t.co/GgJjTi8KwB Tree-SNE that can perform hierarchical clustering. That is realized by arranging one dimension t-SNE with reducing both the perplexity and the degree of freedom α of t distribution. t.co/aIb9wubSdZ
@upura0 t-SNE & 階層的クラスタリング。GitHub (t.co/sasWO8342U) でコードも公開済。 Tree-SNE: Hierarchical Clustering and Visualization Using t-SNE t.co/zG2xWK4rx4 t.co/JsP9jwCD5q
@lpachter An interesting preprint introducing tree-SNE, which performs hierarchical clustering using (one-dimensional) t-SNE: t.co/0xx3RLa4Xo

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