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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