Sentence examples for measured prediction from inspiring English sources

To measure the susceptibility of functional modules, we measured prediction error rates of functional modules from RF analysis.

We measured prediction accuracy for each pair of 30 training-testing datasets and for a total of 30 predictions (Table 6).

The metric we use here is based on the mean absolute error (MAE) between prediction (SLA imposed) and real response time, which is the normal choice to measure prediction accuracy.

The area under the ROC curve (AUC) can be used to measure prediction performance where 0.5 is random prediction and 1.0 is perfect prediction.

I also present the results from several alternative strategies and discuss the difference between several evaluation methods for measuring prediction accuracy.

For measuring prediction performance, we used the AUC of the receiver operating characteristic (ROC) curve that is most widely used method for measuring prediction performance [ 34, 35].

Instead, utilization of the time-dependent ROC and AUC was used to measure prediction performance [ 13].

Machine learning and multivariate pattern analysis (MVPA) are neuroimaging analysis techniques that can be used to measure prediction accuracy.

To measure prediction performance, accuracy scores were computed as described earlier for each antigen using the TN, TN, FN and FP variables.

To evaluate our methods, maize and wheat data previously used with standard Bayesian regression models were employed for measuring prediction accuracy using the proposed models.

To measure prediction accuracy against a corresponding reference network, we used the AUC [ 20], a single measure that summarizes the trade-off between true positive rate and false positive rate [ 20].