From: Machine Learning Algorithms for understanding the determinants of under-five Mortality
Train/test ratios | Measures | Decision tree | Random forest | Naive Bayes | K-Nearest neighbour | Logistic regression | SVM regression | Neural network | Ridge regression |
---|---|---|---|---|---|---|---|---|---|
70/30 | Sensitivity | 83.90 | 58.40 | 21.83 | 57.78 | 70.59 | 70.23 | 81.03 | 71.43 |
Specificity | 95.53 | 96.05 | 93.73 | 94.04 | 95.55 | 95.55 | 95.75 | 94.33 | |
Precision | 33.21 | 42.16 | 5.27 | 9.56 | 33.82 | 33.82 | 36.64 | 14.09 | |
Accuracy | 95.23 | 94.28 | 92.60 | 93.65 | 94.77 | 94.75 | 95.31 | 94.04 | |
F1 Score | 47.59 | 48.97 | 8.49 | 16.40 | 45.73 | 45.66 | 50.46 | 23.54 | |
Negative Predictive value | 99.56 | 97.91 | 98.68 | 99.51 | 99.02 | 99.00 | 99.40 | 99.61 | |
Cohen’s kappa values | 0.46 | 0.46 | 0.06 | 0.15 | 0.44 | 0.44 | 0.48 | 0.22 | |
80/20 | Sensitivity | 84.3 | 58.40 | 21.21 | 60.00 | 71.79 | 71.64 | 71.51 | 71.68 |
Specificity | 95.60 | 96.05 | 93.70 | 94.01 | 95.67 | 95.62 | 96.25 | 94.36 | |
Precision | 34.43 | 42.16 | 5.13 | 9.34 | 35.90 | 35.16 | 45.05 | 14.84 | |
Accuracy | 95.23 | 94.28 | 92.55 | 93.67 | 94.89 | 94.85 | 95.29 | 94.05 | |
F1 Score | 48.89 | 48.97 | 8.26 | 16.16 | 47.86 | 47.17 | 55.28 | 24.58 | |
Negative Predictive Value | 99.55 | 97.91 | 98.67 | 99.56 | 99.01 | 99.03 | 98.74 | 99.59 | |
Cohen’s kappa values | 0.47 | 0.46 | 0.06 | 0.15 | 0.46 | 0.45 | 0.53 | 0.23 |