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. 2018 Jul 30;18(8):2464. doi: 10.3390/s18082464

Table 2.

Model results and analysis using training and validation datasets. TP: true positive, TN: true negative, FP: false positive, FN: false negative, SST: sensitivity, SPC: specificity, ACC: accuracy, T: training; V: validation.

BLR SVM LMT ADTree
T V T V T V T V
TP 16 5 16 4 15 5 14 4
TN 15 6 14 6 14 5 15 5
FP 2 1 2 1 3 2 2 2
FN 1 2 3 3 2 2 3 3
SST 0.941 0.714 0.842 0.571 0.882 0.714 0.824 0.571
SPC 0.882 0.857 0.875 0.857 0.824 0.714 0.882 0.714
ACC 0.912 0.786 0.857 0.714 0.853 0.714 0.853 0.643
Kappa 0.822 0.571 0.764 0.571 0.764 0.428 0.764 0.428
RMSE 0.297 0.426 0.323 0.430 0.335 0.432 0.363 0.462