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Table 3 The clustering performance of the nine methods on single-cell dataset

From: Robust hypergraph regularized non-negative matrix factorization for sample clustering and feature selection in multi-view gene expression data

Methods

K-means

PCA

NMF

GNMF

NMFL2,1

HNMF

SHNMF

RGNMF

RHNMF

AC (%)

76.16 ± 0.18

76.89 ± 0.64

77.19 ± 0.64

78.57 ± 0.47

78.15 ± 0.32

79.19 ± 0.26

78.36 ± 0.45

79.76 ± 0.13

80.94 ± 0.07

NMI (%)

38.29 ± 0.22

36.34 ± 0.77

38.27 ± 0.73

39.63 ± 0.53

41.05 ± 0.10

40.39 ± 0.26

39.12 ± 0.57

40.78 ± 0.04

41.19 ± 0.03

  1. Note: The best experimental results are highlighted in italics