Table 1 Results of CBR and DT RBR on heart disease dataset
From: Building an enhanced case-based reasoning and rule-based systems for medical diagnosis
Approach | Accuracy | Precision | Recall | F1-Score |
|---|---|---|---|---|
Cosine similarity | 100% | 100% | 100% | 100% |
Euclidean distance | 98.54% | 97% | 100% | 99% |
Manhattan distance | 98.54% | 97% | 100% | 99% |
Pearson correlation coefficient | 100% | 100% | 100% | 100% |
Jaccard similarity | 84.39% | 86% | 82% | 84% |
Dice coefficient | 84.39% | 86% | 82% | 84% |
Logistic regression similarity | 100% | 100% | 100% | 100% |
Random forest similarity | 100% | 100% | 100% | 100% |
GaussianNB similarity | 98% | 97% | 100% | 98% |
DT RBR | 100% | 100% | 100% | 100% |
HRFLM [8] | 88.4% | 90.1% | 92.8% | 90% |
SVM approach [9] | 92.3% | 92.55% | 92.43% | N/A |