Research Article
Voting Classification-Based Diabetes Mellitus Prediction Using Hypertuned Machine-Learning Techniques
| | Classifier/algorithm | Technique | Accuracy % | ROC % |
| | Logistic regression | Default
Tomek- undersampling
Smote- oversampling | 77.7
77.0
76.7 | 68.3
69.7
76.5 | | SVM | Default
Tomek- undersampling
Smote- oversampling | 79.2
77.7
7.2 | 71.2
70.2
70.3 | | KNN | Default
Tomek- undersampling
Smote- oversampling | 74.5
78.2
77.5 | 66.5
73.3
77.9 | | Gradient boost | Default
Tomek- undersampling
Smote- oversampling | 79.4
77.0
77.9 | 71.6
72.0
78.0 | | Naive Bayes | Default
Tomek- undersampling
Smote- oversampling | 79.7
75.5
73.9 | 73.1
72.0
73.8 | | Random Forests | Default
Tomek- undersampling
Smote- oversampling | 79.7
75.9
80.7 | 73.5
69.8
80.6 | | Voting classifier (using three best models as an input) | Default
Tomek- undersampling
Smote- oversampling | 81.7
77.7
81.5 | 81.6
76.5
81.5 |
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