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Step 2. Estimate τ1 for the two-piece exponential model using the learning set.
Using the learning set, we first performed model selection from which the final selected model gave rise to the linear combination rule.
In our study, these method parameters are tuned by performing an internal 3-fold-cross-validation using the learning set only, because i) it is a commonly recommended strategy [ 31], and ii) there is no reliable "gold standard" for these parameters.
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For the ranking of the modules, we used the learning set from our previous study [ 28], in which we had linked individual protein families to plant biomass degradation, and extended it by 20 additional phenotype-positive organisms.
Additional file 14: Microbial isolate strains (lignocellulose degraders and non-degraders) that were used as the learning set.
Using 44 samples from the learning set, we determined PC1 rt (x) by measuring the Ct values.
Using 119 samples from the learning set, we evaluated the seven multi-class predictors described above by leave-one-out cross-validation (LOO).
A first step computed the optimal threshold to separate the 100 healthy controls from the 100 Alzheimer's disease patients of the learning set, using 10-fold cross validation.
In this section, we describe the learning set used in the test, and evaluate the proposed algorithm by comparing the recognition results of the original image, the cropped image of the recognition target part, and the preprocessed recognition target image.
A probability score of ≥0.5 is assigned to all the disease proteins in the learning set used by DGP.
For example, when using the weighted-CF method on the learning set, the best category (only positive votes) contains 24 conformations.
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