Sentence examples for unbiased performance from inspiring English sources

We show that the modeled metrics not only allow unbiased performance comparison but also provide interesting insight about the impact of different parameters on the behavior of these protocols.

Validation of this result, carried out using the bootstrap technique, after briefly introducing the method, indicates that the resubstitution bias is 1.4%, with a final unbiased performance of about 92%.

Sotomayor et al. (2001) developed a simulation benchmark which represented a continuous flow activated sludge process, in a configuration with pre-denitrification, including the processes of organic matter removal, nitrification and denitrification of domestic effluents, for the unbiased performance evaluation of advanced control methods in wastewater treatment plants.

In order to obtain an unbiased performance estimate for the SNP selection method and classifier of [8], the above methods were applied by repeated 10-fold cross-validation.

In order to assess the unbiased performance of our final SVM classifier, we evaluated its performance on a dataset not used in the training or testing.

The protocol allowed unbiased performance comparisons as, over the group of subjects, we compared the same sets of images classified either as animal, bird or dog.

This further validates our unbiased, performance-based marker selection approach.

In contrast to the average unbiased model performance, these performances are biased because they are tested on the entire dataset from which the WAVE score was derived (that is trained and validated).

We quantified the contribution of each of the factors to cancer classification and provided unbiased classification performance estimates using established unbiased data analysis protocols.

In order to obtain an unbiased prediction performance, the prediction models should be validated in external data.

First, an unbiased predictive performance is provided and is based on the untouched portion of the data during cross-validation of predictive models.