Table 9 Confusion matrix and performance measures for SVM classification of wheat genotypes using DE and PSO algorithms.
From: Ensemble and optimization algorithm in support vector machines for classification of wheat genotypes
Performance statistics | Actual | |||||
|---|---|---|---|---|---|---|
DE-SVM | PSO-SVM | |||||
L | M | H | L | M | H | |
Prediction | ||||||
L | 18 | 2 | 0 | 19 | 1 | 0 |
M | 2 | 22 | 0 | 1 | 23 | 0 |
H | 0 | 1 | 14 | 0 | 1 | 14 |
Sensitivity | 0.900 | 0.880 | 1.000 | 0.950 | 0.920 | 1.000 |
Specificity | 0.949 | 0.941 | 0.978 | 0.974 | 0.971 | 0.978 |
Positive predictive value | 0.900 | 0.917 | 0.933 | 0.950 | 0.958 | 0.933 |
Negative predictive value | 0.949 | 0.914 | 1.000 | 0.974 | 0.943 | 1.000 |
Balanced accuracy | 0.924 | 0.911 | 0.989 | 0.962 | 0.945 | 0.989 |
F-measure | 0.900 | 0.898 | 0.966 | 0.950 | 0.939 | 0.966 |
