In a previous work [22] we proposed to adapt the weighted-kernel SVM using a GA instead of the gradient descent algorithm to improve model selection on weighted radial basis kernels rather than to select variables.
We apply the proposed criterion, MW method, AIC and BIC for model selection on arboreal marsupials data.
Furthermore, cross-validation model selection on the number of phases K in the Coxian indicates that only a small K is required to achieve the optimal performance.
To attribute the effect of input parameter and the model selection on the results, both sensitivity and robustness analyses are listed as criteria in the ESS transparency checklist.
Third, we introduce the sequential forward floating search (SFFS) algorithm to perform model selection on multiple-permutation models, gaining further performance improvement.
To determine the evolutionary repercussions of avian culling on host resistance and influenza virulence, we model selection on a dominant allele that confers resistance against influenza.
In our model, selection on the offspring stage of generation t does not affect parental traits (generation t−1) because these individuals belong to different generations.
We resample the input conditions with replacement and run model selection on the new dataset.
In his model, selection on codons is very strong and mutation of codons is negligible.
