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In this study, we propose an algorithm for stably selecting key variables on class-imbalanced data based on the precision-recall curve (PRC), where the PRC is utilized as the assessment criterion in the model building stage, and sparse regularized logistic regression combined with subsampling (SRLRS) is designed to perform stable variable selection.
The performance of the system with varying SNR conditions is considered systematically from the feature extraction and model building stage to the testing stage.
In the model building stage, initial molecular structures are constructed by assembling fragment templates, which are generated from fragmentation of the input molecular graph along sigma bonds.
Fragment sampling in the OMEGA model building stage helps to ensure that flexible ring systems are appropriately examined to find all unique ring conformations.
The type of fragment force field used during the model building stage caused minor variations (less than 0.01) in the average RMSD of conformer models for energy windows 5 and 10 kcal/mol and these disappear entirely at 15 kcal/mol, indicating an overall insensitivity to the type of fragment force field used.
The different stages of model building are the selection stage, consensus stage, deduction stage, model building stage, model testing stage, the model evaluation stage, and the induction stage.
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Marital status and the HoNOS problem with drinking or drug-taking item were initially retained, but were removed during the subsequent model building stages (p = 0.06 for addition of marital status to the final model; p = 0.12 for addition of the HoNOS problems with drinking or drug-taking item).
Four modelling designs were applied: (1) a landscape as a continuous study area without any discrimination between terrestrial and aquatic realms, (2) a stream network masked a posteriori from the previous design, (3) a stream network as the study area during the model-building stage, and (4) same as (3) but with a hydrologically corrected set of predictors.
We also examined as covariates working status and length of time at residence, although neither was observed to be significant, or even close to significant, in the model-building stage.
All variables that were associated with ESBL colonization in the bivariable analysis at the p<0.1 level were included in the model-building stages of the multivariable analysis.
The alignment plays a particularly pivotal role in comparative modeling: if the target-template alignment contains errors, it is extremely difficult to correct them in either the model building or the refinement stage.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com