Criteria | Ambre et al. (2015) [ref] [15] | Mayhew et al. 2015 [ref] [29] | Ahmed et al. 2014 [14] | Zhang et al. 2014 [18] | Axelrad et al. 2013 [25] | Eldardiry et al. 2013 [22] | Parveen et al. 2013 [12] | Brdiczka et al. 2012 [24] | Chen et al. 2012 [13] | Raissi-Dehkordi et al. 2011 [21] | Eberie et al. 2009 [27] | Tang et al. 2009 [26] | Yu et al. 2006 [23] |
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Explain and justify the design and choice of components used in the proposed algorithma | 2 | 3 | 2 | 3 | 1 | 3 | 3 | 3 | 2 | 3 | 3 | 4 | 4 |
A clear description of the exact features used to train the proposed algorithm is givena | 3 | 1 | 1 | 4 | 1 | 3 | 4 | 3 | 4 | 4 | 4 | 2 | 4 |
Feature selection method is cleara | 4 | 3 | 5 | 3 | 4 | 3 | 3 | 1 | 4 | 4 | 4 | 2 | 4 |
Model parameter optimization method is cearly describeda | 3 | 3 | 5 | 1 | 3 | 2 | 3 | 1 | 4 | 4 | 5 | 2 | 4 |
A pseudocode of the proposed algorithm is presenteda | 1 | 1 | 1 | 3 | 1 | 3 | 4 | 3 | 4 | 4 | 4 | 4 | 4 |
The proposed algorithm is compared with the benchmark algorithmsb | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 5 | 5 | 0 | 5 | 5 |
The benchmark algorithms are chosen carefullya | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 2 | 3 | 0 | 3 | 4 |
Detailed evaluation results are provideda | 1 | 5 | 4 | 1 | 2 | 3 | 4 | 3 | 4 | 3 | 5 | 1 | 5 |
The key characteristcs of the experimental dataset are clearly describeda | 2 | 1 | 1 | 3 | 1 | 2 | 3 | 3 | 3 | 3 | 4 | 1 | 5 |
The experimental data are made available to other researchersb | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 5 | 0 | 0 |
Sum | 16 | 17 | 19 | 18 | 13 | 19 | 36 | 17 | 32 | 33 | 34 | 24 | 39 |