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Table 2 Parameter estimation

From: Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data

method dim neighbors/σ loo-cv accuracy
PCA 14 - 87.4
KPCA 15 5e5 87.1
LLE 12 14 88.5
IM 8 10 85
IM(mod) 15 4 87.4
LEM 5 4 85.3
DM 13 5e5 84.3
MVU 5 14 85
  1. All parameters of the dimension reduction techniques for the Wang et al. breast cancer dataset, estimated by leave-one-out cross-validation. PCA has no additional parameter, while KPCA and DM have a kernel parameter σ and IM, LEM and MVU take the number of neighbors as argument.