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. 2012 Apr 3;39(4):2275–2289. doi: 10.1118/1.3682173

Figure 6.

Figure 6

Demonstration of dimension reduction of 3D clusters (a) from 3 to 2 dimensions using Multidimensional Scaling (MDS), Principal Component Analysis (PCA), Locally Linear Embedding (LLE), Isomap and diffusion maps (DfM). Sigma for DfM was 0.2. Neighborhood size for LLE and Isomap, respectively, were 5 and 10. In this example, all methods except LLE were able to preserve clusters in the reduced dimension. Isomap was not able to fully preserve structure of for the cyan color cluster in the embedding space. LLE was not able to preserve structure of all three clusters and converted the clusters to points in the embedding space.