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Table 1 The performance of different models on three species data sets

From: Higher-order partial least squares for predicting gene expression levels from chromatin states

  Linear model Random forest Support vector machine NPLS(41bins) NPLS(21bins)
Hum 0.769(2.43) 0.775(2.46) 0.774(2.46) 0.784(2.37) 0.787(2.35)
Chi 0.756(2.52) 0.767(2.47) 0.765(2.53) 0.780(2.41) 0.784(2.39)
Rhe 0.760(2.52) 0.761(2.51) 0.765(2.54) 0.774(2.46) 0.778(2.43)
  1. Note: The number in bracket following the average R represents averaged RMSE over 10-flod cross validation (with 10 random splitting replicates). Hum: Human data set, Chi: Chimpanzee data set, and Rhe: Rhesus Macaque data set