Data Mining based Techniques | Correctly Classified Instances (%) | Incorrectly Classified Instances (%) | TP (True Positive) Rate | FP (False Positive) Rate | Precision | Recall | F1 Score | |
Experiment I (Variable length) | 100.00% | 0.00% | 1 | 0 | 1 | 1 | 1 | |
Experiment II (Variable length) | 0.00% | 100.00% | 0 | 1 | 0 | 0 | 0 | |
Experiment III (Equal length) | 100.00% | 0.00% | 1 | 0 | 1 | 1 | 1 | |
Chen et al. [16] ―J48 before alignment | Training | 85.00% | 15.00% | - | - | - | - | - |
5-fold cross validation | 60.00% | 40.00% | - | - | - | - | - | |
10-fold cross validation | 63.33% | 36.67% | - | - | - | - | - | |
15-fold cross validation | 68.33% | 31.67% | - | - | - | - | - | |
20-fold cross validation | 60.00% | 40.00% | - | - | - | - | - | |
Chen et al. [16] ―J48 after double alignment | Training | 96.67% | 3.33% | - | - | - | - | - |
5-fold cross validation | 78.33% | 21.67% | - | - | - | - | - | |
10-fold cross validation | 66.67% | 33.33% | - | - | - | - | - | |
15-fold cross validation | 70.00% | 30.00% | - | - | - | - | - | |
20-fold cross validation | 63.33% | 36.67% | - | - | - | - | - | |
Kumar et al. [44] | Existing (known)dataset (Average) | 95.9752% | 4.0248% | 0.96 | 0.094 | 0.962 | 0.96 | 0.959 |
New (unknown)dataset (Average) | 86.6873% | 13.3127% | 0.867 | 0.275 | 0.872 | 0.867 | 0.858 | |
Prabha et al. [45] | - | - | - | - | - | - | - | - |
Statistical method by Srakaew et al. [18] | Reference Set | 98.9167% | 1.0833% | - | - | - | - | - |
Application Set | 95.0477% | 4.9523% | - | - | - | - | - | |
10-fold cross validation | 95.333% | 4.667% | - | - | - | - | - | |
Abstract assembly method by Srakaew et al. [18] | Reference Set | 99.75% | 0.25% | - | - | - | - | - |
Application Set | 98.39% | 1.661% | - | - | - | - | - | |
10-fold cross validation | 99.5% | 0.5% | - | - | - | - | - |