Table 13.
The results of different techniques in terms of accuracy along with the rank values (it ranks the technique for each dataset separately, the best performing algorithm getting the rank of 1 and the second-best rank 2. Last two columns present the sum and average of ranks for each technique.).
| SVM | J48 | RF | MLP | RBF | HMM | CDT | A1DE | NB | KNN | |
|---|---|---|---|---|---|---|---|---|---|---|
| AR1 | 91.73 (2.5) | 90.08 (4.25) | 90.08 (4.25) | 90.08 (4.25) | 91.73 (2.5) | 92.56 (1.5) | 92.56 (1.5) | 90.90 (3) | 85.12 (5) | 90.08 (4.25) |
| AR3 | 88.88 (5) | 87.30 (6.33) | 92.06 (3.5) | 93.65 (2) | 87.30 (6.33) | 97.30 (1) | 87.30 (6.33) | 92.06 (3.5) | 90.47 (4) | 85.71 (7) |
| CM1 | 89.55 (2.5) | 87.95 (5) | 89.15 (4) | 87.55 (6) | 89.55 (2.5) | 90.16 (1) | 89.35 (3) | 86.34 (7) | 85.34 (8) | 84.39 (9) |
| JM1 | 81.74 (4) | 79.93 (8) | 82.66 (1) | 81.96 (3) | 82.02 (2) | 18.33 (10) | 81.65 (5) | 81.47 (6) | 81.41 (7) | 77.08 (9) |
| KC2 | 82.75 (6) | 81.41 (7) | 83.33 (4.5) | 84.67 (1) | 83.71 (2) | 79.50 (9) | 82.95 (5) | 83.33 (4.5) | 83.52 (3) | 80.45 (8) |
| KC3 | 81.95 (1.5) | 79.38 (4) | 81.44 (2) | 77.31 (7) | 79.89 (3.5) | 18.55 (9) | 81.95 (1.5) | 79.89 (3.5) | 78.86 (6) | 72.16 (8) |
| MC1 | 99.28 (5.33) | 99.36 (4) | 99.48 (1.5) | 99.41 (2) | 99.28 (5.33) | 99.28 (5.33) | 99.37 (3) | 98.21 (6) | 94.15 (7) | 99.49 (1.5) |
| Sum (accuracy) | 615.93 | 605.43 | 618.23 | 614.66 | 613.52 | 495.70 | 615.16 | 612.24 | 598.90 | 589.39 |
| Average (accuracy) | 87.99 | 86.49 | 88.32 | 87.81 | 87.65 | 70.81 | 87.88 | 87.46 | 85.56 | 84.20 |
| Sum (rank) | 26.83 | 38.58 | 20.75 | 25.25 | 24.16 | 36.83 | 25.33 | 33.50 | 40.00 | 46.75 |
| Average (rank) | 3.83 | 5.51 | 2.96 | 3.61 | 3.45 | 5.26 | 3.62 | 4.79 | 5.71 | 6.68 |