We improve the model selection process by storing all the models selected in any iteration and applying Occam's window to this cumulative set of models as the last step in the algorithm.
Therefore, all dating analyses must involve a model selection process using Bayes factors to select between a Yule or birth-death prior, in particular on ancient clades with a potential pattern of high extinction.
The variables (and their estimated coefficients) in the final selected bluefin and yellowfin models after the model selection process can be seen in Tables 2 and 3, respectively.
In the final model selection process, a maximum of one hyperparameter value is allowed to be selected from each variable to avoid multicollinearity and effectively optimize the hyperparameter.
McCullagh and Barry [ 21] proposed a model selection process algorithm and recommended to fit different distributions to the data to select the best one by using one of the available information criteria.
Hence the results from the empirical semi-variograms confirmed the results from the model selection process.
The model selection process is categorised into: Kernel selection; Parameter grid search; Feature selection.
Matter of factly, the predictions of the validation objects produce the error estimate that is to be minimized in the model selection process, which shows that the validation objects are not independent of the model selection process.
However, in many practical applications, it needs an expansive model selection process to obtain a correct model structure.
We developed a statistical model selection process using Akaike's Information Criterion AICC) and repeated cross-validation (CV).
When the power-law hypothesis is not rejected, Clauset et al. [1] employ a model selection process to determine the best model for the data.
