Table 2 Results of CBR and DT RBR on the breast cancer coimbra dataset
From: Building an enhanced case-based reasoning and rule-based systems for medical diagnosis
Approach | Accuracy | Precision | Recall | F1-Score |
|---|---|---|---|---|
Cosine similarity | 62.5% | 62% | 67% | 64% |
Euclidean distance | 54.167% | 57% | 33% | 42% |
Manhattan distance | 58.33% | 62% | 42% | 50% |
Hamming distance | 50% | 50% | 100% | 67% |
Pearson correlation coefficient | 62.5% | 62% | 67% | 64% |
Jaccard similarity | 50% | 50% | 100% | 67% |
Dice coefficient | 50% | 50% | 100% | 67% |
Logistic regression similarity | 71% | 71% | 71% | 71% |
Random forest similarity | 92% | 92% | 92% | 92% |
GaussianNB similarity | 75% | 78% | 75% | 74% |
DT RBR | 83% | 88% | 81% | 82% |
KMC AdaBoost [7] | 91.37% | 91.9% | 91.4% | 91.4% |