However, according to the suggested MODI score for regression problems [53], in the automated QSAR modeling workflow (Additional file 1: Figure S1), we suggest a MODI score to be > 0.45 for reaching a model with acceptable predictability (PVE (ge 0.60)).
In the second case, reaching a model end connects the two portions of sequence, leaving only a single uninterrupted subsequence x w..ϵ.
In this paper, through library based researches, we have tried to reach a model of well-organized pedestrian movement, and to clarify safety factors in addition to designing a people-friendly, urban public space.
When thinking of MDE, the immediate understanding is that models drive software development, in the sense that the software is constructed by transforming models from higher levels of abstraction to the point where we reach a model which is executable with the desired degree of quality characteristics.
Eventually, we reached a model in which all terms were statistically significant.
Finally, we ran multivariable logistic regression models by gender with increasing significance values, retaining potential confounders (income, education, race, age, gender), until we reached a model where all additional predictors were significant at P<0.05.
We finally reached a model containing VKORC1, CYP2C9*2 and *3, PROC, EPHX1, GGCX, ORM1-2, age, bodyweight and drug interactions which explained 73% of the variance in warfarin dose (Table 4).
This semantic model is transformed by abstraction functions (ABS*), until reaching a finite model suitable for model-checking.
Backward elimination (deleting the covariate with the largest P value, one at a time) was performed from the initial model until we reached a final model with statistically significant covariates.
Independent variables of each block were adjusted for each other, and those that remained significant at 5% (p ≤ 0.05) were retained in the analysis for adjustment in the next model to reduce discrepancy between the data and the model and reach an economic model with relatively few parameters [ 87].
This criterion was used to reduce discrepancy between the data and the model and reach an economic model with relatively few parameters.
