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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