Sentence examples for model generalization capacity from inspiring English sources

LOO procedure gives a reliable estimate of the prediction error with less bias than other cross-validation methods and it allows good control of model generalization capacity using all available data for training.

A key element in statistical discrimination is the model's generalization capacity, which is estimated by the model's performance on a test set that is not used for training.

According to the results, the PSO algorithm successfully improved the RBFN while the RBFN-PSO model's generalization capacity enhanced, with RMSE of 0.071 compared to the RBFN-BP model with RMSE of 0.114 in the testing dataset.

Finally, testing data were used to evaluate the model's generalization capacity.

Unlike the standard approaches to perception, we argue that this mapping draws on internal causal and compositional models of the physical world and these internal models underlie the generalization capacity of human perception.

In mSVDD, we leverage the probabilistic framework with kernel-based method, where the model comprises two quantities: log likelihood to control the fit of data to the model (i.e., empirical error) and regularization quantizer to control the generalization capacity of the model (i.e., general error).

The results revealed that the proposed models have good prediction and generalization capacity with acceptable errors.

end{aligned} (4)In the optimization problem as shown in Eq. (4), we minimize (sum _{j=1}^{m}R_{j}^{2}) to maximize the generalization capacity of the model.

The generalization capacity of the model was ensured by selecting the weights resulting in the least test set RMSE. Figure 3 shows a comparison between calculated and experimental values of the output variable for data set by using neural network model.

In addition, besides classification accuracy, the robustness and learning generalization capacity of the SVM model is superior to the BP neural network model.

The adoption of a graph-type representation allows the inclusion of the physico-chemical properties of amino acids, which increases the generalization capacity of the models.