Skip to main content

Table 1 Evaluation of the clustering performance of the two t-SNE results in Fig. 2. As a reference, the compression rate from 15,975 features down to 200 supersets is about 98.7%

From: GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization

Index Method t-SNE of
15,975 genes
t-SNE of
200 supersets
Compression lossa
Dunn index 0.247 0.189 23.48%
Silouette index 0.355 0.358 −0.85%
IID index 7.924 8.125 −2.54%
  1. aThe compression loss = (index score of genes – index score of supersets) / index score of genes