Table 2.
Average accuracy and standard deviation (in parentheses) for the performed experiment
| Weka classification method | Description | No feature selection | CFS | InfoGain | Consistency |
|---|---|---|---|---|---|
| J48 | Decision trees | 75.50 | 75.90 | 76.13 | 58.70 |
| (26.28) | (25.84) | (25.47) | (25.57) | ||
| PART | Rule based classifier | 67.67 | 69.03 | 70.07 | 56.67 |
| (22.74) | (23.01) | (23.10) | (26.00) | ||
| Bayes Net | Bayesian netwoks | 91.47 | 93.40 | 91.47 | 82.50 |
| (15.23) | (15.60) | (15.23) | (24.63) | ||
| Naive Bayes | Naïve Bayes classifier | 54.23 | 79.40 | 75.43 | 62.20 |
| (25.61) | (23.16) | (23.53) | (27.58) | ||
| Multilayer | Neural netwoks | 52.53 | 64.63 | 65.90 | 58.07 |
| Perceptron | (26.93) | (25.69) | (24.70) | (27.12) | |
| IBk | K-nearest neighbours | 43.23 | 64.00 | 68.93 | 54.67 |
| (25.24) | (25.17) | (28.01) | (28.93) | ||
| Kstar | Instance-based learner | 40.70 | 68.33 | 62.83 | 60.30 |
| using an entropic distance measure | (25.62) | (23.76) | (23.48) | (27.95) | |
| SVM | Support vector machine | 65.33 | 63.67 | 60.97 | 46.17 |
| (SVM) with C-SVM Type | (22.63) | (23.72) | (23.48) | (20.53) | |
| SMO | SVM with sequential | 64.37 | 67.80 | 68.23 | 49.93 |
| minimal optimization | (28.26) | (25.33) | (26.02) | (25.40) |
Best accuracy appears in bold