Sentence examples for both models tend to from inspiring English sources

Starting from 5,000 TU, both models tend to increase the error showing over-training.

Both sets of models, release and yield, predict the 18 external validation samples reasonably well, though both models tend to under estimate accessible carbohydrates at high reactivity.

Both models tended to predict yields satisfactorily, but more accurately for maize, intermediate for sorghum and less accurately for sunflower.

The results showed that under infiltration conditions, both models tended to under-estimate Tc, however, Tc predicted using the GUEST model had better agreement with the measured Tc values than that predicted with WEPP.

Although both models tended to over-predict the risks of long-term unfavourable outcome, the IMPACT model had a slightly better calibration than the CRASH model (intercept of the calibration curve = −4.1 vs. -5.7, respectively), especially when the predicted risks of unfavourable outcome were < 80%%.

In short, incorrect classifications made by both models tended to be optimistic, overestimating survival in most cases.

In both NHANES and ARIC and for both men and women, the models tend to overpredict when WC is small and underpredict when WC is large.

In contrast, for medium H2 content fuels, both measurement techniques show that the models tend to overpredict flame speed, with the discrepancy increasing as Φ decreases and temperature increases.

Weather models tend to project moderate rather than extreme warmth.

Less expensive models tend to be less durable and unreliable.

Climate models tend to be more accurate at predicting temperature than precipitation.