The optimal predictor variable vector(s) (model base variables) was then overlaid as a bi-plot [45].
This paper put forward an optimizing model based on variable precision rough sets (VPRS) for the land cover discrimination in wetland inventory.
To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function.
With the use of BIM and eQUEST, the paper develops a MCDM model based on variable fuzzy Preference ranking organization method for enrichment evaluation (PROMETHEE) to improve the robustness and practicality of decision results over traditional methods.
In conclusion, a model based on variables from clinical registries can identify a group of patients with heart failure who on average will incur higher costs in the first year after hospitalization.
A multivariate logistic regression model based on variables measured within the first 24 h was constructed for prediction of mortality or dialysis.
Classification techniques allow training a model based on variables (e.g. SNPs in genetic association studies) to separate different classes (e.g. healthy subjects versus patients).
We constructed a clinical model based on variables suggested by the referee (age, sex, BNP, LVEF, and creatinine), using as decisional cut-off of the median values of our entire population.
Then, we compared the predictive accuracy of the subset models with the comprehensive model (based on n variables), to eliminate variables that lead to over-fitting and to select key risk factors.
A cost model based on the variable sampling intervals is formulated and analyzed.
In Fig. 3, the hydrodynamic model, based on the variable superficial velocity model presented in Sect.
