Functional value was found to be affected mainly by reliable instances and accuracy of service quality, whereas conditional value was influenced by the responsiveness of service quality.
The common conclusion was that in most instances the accuracy of predicting genotypic values was comparable for the investigated approaches.
Robotic assistance is considered valuable in this instance, owing to higher levels of accuracy and more accurate implant alignment.
This model is based on a multi-fidelity approach, which consists in simulating at different levels of accuracy, for instance by varying the spatial discretization in a CFD solver.
We have shown that COMPARE achieves high accuracy for instances of the human methylome.
In the Critical Assessment of Prediction of Interactions (CAPRI) experiment (Janin et al., 2003), for instance, assessment of the accuracy of the docked models is based on a combination of positional root mean square deviation (RMSD) criteria and conservation of intermolecular contacts with respect to the native structure (Lensink et al., 2007).
For instance, the accuracy of this approach was 8.2% better with respect to the method proposed in [6] when compared on the same dataset.
For instance, the accuracy of predictions is based on material parameters, which are obtained mostly from complicated experimental studies or from the literatures.
For instance, the accuracy of pose recapitulation for known cocrystal complexes leads us to believe that highly scoring covalent docking poses are in productive, on-path conformations, in contrast to the incompatible poses predicted by noncovalent docking (Supplementary Figure 2).
The small number of instances constituting each biological dataset (three instances per dataset) prevents a clear statistical characterization of the performances of CRM2 in terms of accuracy.
From the mining results with the J48 algorithm we evaluate the induced models by typical measures: the rate of correctly classified instances, accuracy (higher values are better), the size of the tree (good values are related to interpretable trees), the root mean-squared error (RMSE), and mean absolute error (MAE) (smaller values are expected).
