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Description: The prediction accuracies of all tested methods were measured using the structure benchmark set.
p.17: Sentence "This should be the results that MEMSAT-SVM has the lowest prediction accuracy on 7 TMHs proteins using the Structure benchmark set" is not clear; please rephrase.
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Using the structure-based BA benchmark of Kastritis et al. (2011), we correlated ICs with experimentally determined BA data (Kd or ΔG) for protein complexes (bound forms).
The following diagrams show the results: As it can be seen, we did not get significantly better or worse topology prediction accuracy by removing the 61 protein used for training the various methods, than in random cases, indicating that the used methods are not overfitted to the structure benchmark set.
We calculated the per-protein topography (AccTpg) and topology (AccTop) accuracies of each method on the "structure benchmark set", and used these values as weights for the constraints.
One option is to use the structure of 'naturally' developed forest as benchmark.
The abstracted networks are compared in terms of their geographical and topological structures using the initial network as a benchmark.
The performance of the presented structure damage classifier has been validated using a benchmark structure proposed by the IASC ASCE (International Association for Structural Control American Society of Civil Engineers Structural Health Monitoring SHM Task Groupoup and a three-story frame provided by Los Alamos National Laboratory.
The presented hybrid immune model (combined with fuzzy clustering and the artificial immune pattern recognition) has been tested using a benchmark structure proposed by the IASC ASCE (International Association for Structural Control American Society of Civil Engineers Structural Health Monitoring Task Groupp.
Numerical results are derived using a benchmark structure made by three aluminum plates with a common junction and a launcher fairing.
Per multiple case study a research protocol was used to structure the benchmarking process.
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