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Table 4 Root yield ML Model comparison

From: Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)

  ML Method PCA PCR PCA vs PCR Difference (%)
R2 RMSE RRMSE R2 RMSE RRMSE R2 RMSE RRMSE
Validation RF 0.93 443.07 9.88% 0.94 449.09 9.19% 1.07% 1.35% 7.24%
SVM 0.67 888.23 20.91% 0.63 947.45 22.10% 6.15% 6.45% 5.53%
kNN 0.64 930.57 21.94% 0.64 953.3 22.01% 0.00% 2.41% 0.32%
ANN 0.69 893.16 20.26% 0.7 910.21 21.12% 1.44% 1.89% 4.16%
Test RF 0.66 889.28 20.52% 0.64 891.86 21.12% 3.08% 0.29% 2.88%
SVM 0.64 916.77 21.23% 0.64 874.13 21.14% 0.00% 4.76% 0.42%
kNN 0.67 899.8 20.10% 0.67 879.09 20.20% 0.00% 2.33% 0.50%
ANN 0.61 1021.81 22.73% 0.61 1120.04 22.61% 0.00% 9.17% 0.53%