Table 3 Results of classification of salinity stress tolerance.
From: Classification and prediction of drought and salinity stress tolerance in barley using GenPhenML
ML models | Phenotype features | Genotype features | Genotype and phenotype features | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Train | Test | Train | Test | Train | Test | |||||||||||||
Accuracy | Precision | F1-score | Accuracy | Precision | F1-score | Accuracy | Precision | F1-score | Accuracy | Precision | F1-score | Accuracy | Precision | F1-score | Accuracy | Precision | F1-score | |
ReliefF algorithm | ||||||||||||||||||
 DT | 0.84 | 0.83 | 0.85 | 0.71 | 0.68 | 0.73 | 0.71 | 0.72 | 0.70 | 0.63 | 0.63 | 0.63 | 0.91 | 0.94 | 0.91 | 0.76 | 0.75 | 0.77 |
 DA | 0.61 | 0.74 | 0.48 | 0.58 | 0.69 | 0.41 | 0.61 | 0.71 | 0.48 | 0.55 | 0.62 | 0.38 | 0.62 | 0.75 | 0.48 | 0.62 | 0.76 | 0.47 |
 NB | 0.83 | 0.87 | 0.82 | 0.71 | 0.69 | 0.72 | 0.76 | 0.78 | 0.75 | 0.66 | 0.66 | 0.66 | 0.87 | 0.91 | 0.87 | 0.78 | 0.79 | 0.78 |
 SVM | 0.95 | 0.95 | 0.95 | 0.73 | 0.71 | 0.74 | 0.78 | 0.82 | 0.77 | 0.61 | 0.62 | 0.60 | 0.90 | 0.88 | 0.90 | 0.79 | 0.75 | 0.80 |
 KNN | 0.95 | 0.96 | 0.95 | 0.91 | 0.95 | 0.91 | 0.97 | 0.98 | 0.97 | 0.89 | 0.89 | 0.89 | 0.98 | 0.97 | 0.98 | 0.96 | 0.98 | 0.96 |
 RF | 0.98 | 0.98 | 0.98 | 0.81 | 0.80 | 0.82 | 0.87 | 0.89 | 0.86 | 0.71 | 0.70 | 0.71 | 0.93 | 0.94 | 0.93 | 0.87 | 0.88 | 0.87 |
 NN | 0.87 | 0.89 | 0.87 | 0.72 | 0.72 | 0.72 | 0.68 | 0.71 | 0.66 | 0.60 | 0.61 | 0.58 | 0.85 | 0.87 | 0.84 | 0.76 | 0.77 | 0.76 |
MRMR algorithm | ||||||||||||||||||
 DT | 0.91 | 0.90 | 0.91 | 0.66 | 0.65 | 0.68 | 0.72 | 0.70 | 0.73 | 0.60 | 0.59 | 0.62 | 0.87 | 0.87 | 0.87 | 0.72 | 0.71 | 0.73 |
 DA | 0.61 | 0.72 | 0.48 | 0.56 | 0.61 | 0.42 | 0.61 | 0.63 | 0.58 | 0.46 | 0.45 | 0.42 | 0.64 | 0.79 | 0.51 | 0.61 | 0.71 | 0.47 |
 NB | 0.81 | 0.85 | 0.80 | 0.64 | 0.59 | 0.72 | 0.82 | 0.85 | 0.81 | 0.63 | 0.58 | 0.71 | 0.84 | 0.88 | 0.83 | 0.71 | 0.73 | 0.70 |
 SVM | 0.96 | 0.96 | 0.96 | 0.81 | 0.79 | 0.82 | 0.99 | 0.99 | 0.99 | 0.72 | 0.68 | 0.74 | 0.99 | 0.99 | 0.99 | 0.85 | 0.82 | 0.85 |
 KNN | 0.97 | 0.98 | 0.97 | 0.84 | 0.82 | 0.85 | 0.90 | 0.88 | 0.90 | 0.76 | 0.74 | 0.77 | 0.99 | 0.98 | 0.99 | 0.98 | 0.99 | 0.98 |
 RF | 0.94 | 0.94 | 0.94 | 0.75 | 0.74 | 0.75 | 0.85 | 0.85 | 0.85 | 0.69 | 0.67 | 0.71 | 0.92 | 0.94 | 0.91 | 0.89 | 0.90 | 0.89 |
 NN | 0.93 | 0.93 | 0.93 | 0.74 | 0.72 | 0.76 | 0.71 | 0.73 | 0.70 | 0.65 | 0.65 | 0.66 | 0.97 | 0.98 | 0.97 | 0.77 | 0.76 | 0.78 |
Chi2 algorithm | ||||||||||||||||||
 DT | 0.89 | 0.87 | 0.89 | 0.68 | 0.66 | 0.69 | 0.72 | 0.69 | 0.74 | 0.62 | 0.60 | 0.66 | 0.91 | 0.90 | 0.92 | 0.73 | 0.69 | 0.75 |
 DA | 0.62 | 0.75 | 0.48 | 0.59 | 0.71 | 0.42 | 0.61 | 0.61 | 0.61 | 0.46 | 0.47 | 0.48 | 0.64 | 0.79 | 0.51 | 0.61 | 0.71 | 0.47 |
 NB | 0.81 | 0.84 | 0.80 | 0.68 | 0.70 | 0.67 | 0.88 | 0.91 | 0.87 | 0.60 | 0.56 | 0.69 | 0.99 | 0.99 | 0.99 | 0.79 | 0.80 | 0.78 |
 SVM | 0.95 | 0.96 | 0.95 | 0.78 | 0.76 | 0.78 | 0.88 | 0.87 | 0.88 | 0.73 | 0.71 | 0.74 | 0.99 | 0.99 | 0.99 | 0.86 | 0.84 | 0.86 |
 KNN | 0.95 | 0.96 | 0.95 | 0.82 | 0.81 | 0.83 | 0.82 | 0.85 | 0.82 | 0.79 | 0.79 | 0.79 | 0.93 | 0.94 | 0.93 | 0.96 | 0.98 | 0.96 |
 RF | 0.99 | 0.99 | 0.99 | 0.81 | 0.84 | 0.80 | 0.82 | 0.82 | 0.82 | 0.72 | 0.72 | 0.73 | 0.91 | 0.90 | 0.92 | 0.86 | 0.87 | 0.86 |
 NN | 0.98 | 0.98 | 0.98 | 0.71 | 0.70 | 0.72 | 0.76 | 0.80 | 0.75 | 0.62 | 0.64 | 0.60 | 0.98 | 0.98 | 0.98 | 0.75 | 0.73 | 0.76 |