Research Article
CBO-IE: A Data Mining Approach for Healthcare IoT Dataset Using Chaotic Biogeography-Based Optimization and Information Entropy
Table 2
Average ranking of all algorithms based on intracluster distance.
| Dataset | K-Means | GA | PSO | ALO | BO | CBO-IE |
| Thoracic surgery | 3.364 (5) | 0.7569 (4) | 0.4256 (4) | 0.2547 (3) | 0.0657 (2) | 0.00652 (1) | Breast cancer | 26.265 (5) | 0.8634 (4) | 0.3126 (4) | 0.2614 (3) | 0.0874 (2) | 0.00728 (1) | Cryotherapy | 24.3640 (5) | 0.4562 (4) | 0.2864 (4) | 0.2167 (3) | 0.0725 (2) | 0.00548 (1) | Liver patient | 35.3245 (5) | 0.5863 (4) | 0.1567 (4) | 0.1321 (3) | 0.0635 (2) | 0.00457 (1) | Heart patient | 14.2366 (5) | 0.9362 (4) | 0.7265 (4) | 0.6492 (3) | 0.0623 (2) | 0.00832 (1) | Chronic kidney disease | 46.3625 (5) | 0.5682 (4) | 0.3568 (4) | 0.2864 (3) | 0.0742 (2) | 0.00786 (1) | Diabetic retinopathy | 0.3658 (5) | 0.2526 (4) | 0.1737 (4) | 0.1421 (3) | 0.0967 (2) | 0.00758 (1) | Blood transfusion | 0.6745 (5) | 0.5684 (4) | 0.2375 (4) | 0.2068 (3) | 0.0854 (2) | 0.00852 (1) | Average ranking () | 5 | 4 | 4 | 3 | 2 | 1 |
|
|