Sentence examples for minimum expected error from inspiring English sources

[14] describe an optimal solution for pool-based active learning that selects the instance that, once labeled and added to the training set, produces the minimum expected error.

The published criteria are generally based on target accuracy, classifier confidence, uncertainty estimation, and minimum expected error.

For each model variant, we designed a selection experiment to identify the best configuration of parameters as the one that achieves the minimum expected predictive error.

The oblique dashed lines in Figure 9 B indicate the expected error ranges that were estimated from the minimum CV.

The best tree was chosen using the minimum cross-validation criterion, which chooses the tree with the lowest expected error if new data were to be applied to this model (cross-validated error) [ 19].

A possible optimal network distribution which is less sensitive to the change of scenarios and has the minimum total annual cost is achieved by the tradeoff between the total annual cost and the expected error.

And while some human error is normal, and to be expected, error inherently means that the process was not perfect.

This corresponds to estimated expected error.

These learning curves are usually well characterized by inverse power-laws: <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0012781.e001.PNG" class= inline-graphic"/> The variables are the expected error rate e(n) given n training samples, the learning rate a, the decay rate α, and the Bayes error b which is the minimum error rate achievable.

All filled marks were within the expected error ranges.

Then, just as in least squares, the dosage regimen is iteratively optimized until the regimen hitting the target with the minimum expected weighted squared error is found.