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Official Journal of the Japan Wood Research Society

Table 2 Accuracy of regular CNN in prediction of specimen’s ORP and ρ

From: Potential of machine learning approaches for predicting mechanical properties of spruce wood in the transverse direction

Splitting method for regular CNN

Group

ORP (°)

Density (g/cm3)

R2

RMSE

R2

RMSE

Method #1

Train

0.991 (0.004)

2.4 (0.6)

0.674 (0.102)

0.034 (0.005)

Test

0.972 (0.008)

4.4 (0.4)

0.357 (0.061)

0.048 (0.003)

Method #2

TrainA2,B1,B2

0.990

2.7

0.809

0.021

TestA1

0.892

8.9

− 469.166

0.112

TrainA1,B1,B2

0.986

3.0

0.677

0.039

TestA2

0.927

6.9

− 4.211

0.049

TrainA1,A2,B2

0.986

3.5

0.073

0.056

TestB1

0.973

3.4

− 10.321

0.045

TrainA1,A2,B1

0.986

3.1

0.053

0.049

TestB2

0.975

4.1

− 5.815

0.085

  1. The values in parentheses indicate the standard deviation