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Penguin population trends are independent of model development (see below) and were only used to evaluate model predictions.
A χ2 test was used to evaluate model fit, by determining whether the covariance structures implied by the model adequately fit the actual covariance structures of the data.
Cross-validation procedure was used to evaluate model performance and uncertainty.
Analysis of variance (ANOVA) was used to evaluate model fitness and determine optimal conditions.
Finally, whey protein isolate was used to evaluate model parameters in real conditions.
Triaxial tests of concrete cubes are used to evaluate model parameters.
Similar(25)
Different statistical errors functions are used to evaluate models and determine the most accurate one.
A potential function was generated from these observations and used to evaluate models for novel disulfide bonds in human carbonic anhydrase II (HCAII).
This dataset was used to evaluate models for ranking detected cavities and to determine a threshold above which detected cavities constitute potential binding sites.
Likelihood ratio tests were used to evaluate models with the interaction terms compared with models without the interaction terms and reviewed for trends.
10-fold cross-validation approach was used to evaluate models created by different machine learning, including ANN, LR, SVM, and RF.
More suggestions(15)
used to evaluate models
used to evaluate patient
used to evaluate fatigue
used to evaluate survival
used to evaluate treatment
used to evaluate publication
used to evaluate response
used to evaluate risk
used to evaluate energy
used to evaluate heterogeneity
used to evaluate chemical
used to evaluate drug
used to evaluate tissue
used to evaluate blood
used to evaluate reliability
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