Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions.
We note that for the dataset in question, the initial R-squared value is close to 0.38, and upon completion of the algorithm R-squared is approximately 0.75.
In both datasets, the initial number of sequences is around 5000, but after pruning the datasets are significantly smaller, with less than one-third of the sequences retained in the PDZ dataset and a mere one-sixth retained in the CS dataset.
For this illustration, we simulated multiple datasets with the initial values presented in Figure 6(b), which could easily reflect actual experimental settings.
The automatic experiment points out that NSGA-II overalld overall superiority in two of the three datasets investigated, positioning itself as a good search technique for smaller scenarios, while IBEA showed a better performance for large datasets, since the loss in the initial diversity of the algorithm decreases as the number of requirements increases.
As shown in Fig. 4, Apriori algorithm produces removable candidate datasets C (candidate itemset) that have high frequency in the database D, and extends them to longer datasets L (large itemset) consisted from candidate datasets C. Note that the initial datasets in the database satisfy an essential prerequisite for performing trilateration, one of constraints.
Those with uncertain or unknown pathogenicity were removed from the dataset and not considered in the initial analysis.
Full-sib family was fitted as a fixed effect in the line-cross model in the larger dataset (but was omitted in the initial analysis).
The new dataset contained 16,511 observations, 2,038 of the positive (1,372 positive in the initial dataset + 666 positive to any of the other diseases).
In these within-dataset experiments, the initial set of top 50 markers have been selected using the entire dataset, in order to reduce the effect of sensitivity in marker selection when comparing different pathway-based methods.
