Sentence examples for validation considered from inspiring English sources

Experimental validation considered a 16-core architecture comparing our proposal with different settings of threshold-based policies.

The original study of ALQ validation considered an American and Chinese sample (Walumbwa et al. 2008) and attempted to break with the hegemony of North American research into leadership.

Three parts will be conducted, consisting of translation and crosscultural adaptation of the SRI into German, a subsequent evaluation in a pilot trial and a validation considering aspects of construct validity, incremental validity, predictive validity, aspects of reliability and structure of the instrument.

The results show that model architecture selection is the best implemented step, while greater focus should be given to input selection considering input independence and model validation considering replicative and structural validity.

On the one hand, this validation considers the development of two ITS applications using CAM and DENM functionalities for tracking vehicles and disseminating traffic incidences.

This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model.

On the one hand, it's frustrating because the young company isn't in a position to get into a bidding war with Consumer Reports, but on the other hand it's a point of validation, considering that one of the biggest names in the space is willing to put money down on people searching for the company — or people misspelling consumer, either way.

This approach enables validation considering the stoichiometric balances and also reactions reversibilities, and accounting for measurements imprecision.

To see why holdout has higher variance than repeated 10-fold cross-validation, consider that there are several major sources of variance of estimators in practical use.

Only 3 validation studies considered prediction rules when validating the models and overall the models were validated using varied tests in distinct populations, which made direct comparisons difficult.

The shrinkage between training and validation sample (R– R) was 0.017 (≤2%), and validation was considered successful.