This model selection method is designed to yield the model which provides the best multistep forecast for the given lead time, without assuming that the process actually obeys a FEXP model.
Our model selection strategy was designed to address a single research question: Is there evidence of an association between prenatal exposure to DDTs and hypertension?
Since the number of dose levels are important for model selection study design is important and should be further evaluated.
In this paper, the reverse flow reactor model selection for design purposes has been identified using a case-based reasoning tool capable of interactive querying and abstraction procedure.
These efforts, as a whole, high-light common challenges in animal model selection, study design, interpretation, and reporting which go beyond individual disease states.
In this paper, we first present a self-training semi-supervised support vector machine (SVM) algorithm and its corresponding model selection method, which are designed to train a classifier with small training data.
With this analysis, new iterative parameter estimation and model selection techniques can be designed and implemented [ 17, 32].
Model selection via uniform design can effectively alleviate the computational cost, but its drawback is that it adopts a single objective criterion which can not always guarantee the generalization capacity.
There is a large amount of variation in neuropathology, natural history and drug sensitivity (Whittle et al, 1998; Candolfi et al, 2007; Zhang et al, 2010) and this underpins the importance of glioma model selection during experimental design.
I would suggest that the claim about "designing model selection approach" is toned done, as the authors themselves state in the response letter that "we do not claim to provide any notable advances in this paper for the computational community".
