Sentence examples for mean error mean from inspiring English sources

Most of the improvements were at the slight to moderate levels, e.g., 3.66 14.24% increases in the accuracy based on mean error, mean absolute error, root mean square error and R2.

Our model performs better than the existing models as reported by mean error, mean absolute error and mean square error.

Table 3 shows mean error, mean absolute error and mean square error of predicted compared to actual utility scores by EQ-5D utility range for existing approaches [ 3, 4].

Predictive ability is assessed using line graphs of the observed and predicted EQ-5D utility scores ordered by observed tariff value of EQ-5D state, mean error, mean absolute error and mean squared error.

Note: * significant at 1% Table 3 reports mean error, mean absolute error (MAE) and mean squared error (MSE) of predicted compared to actual utility scores by EQ-5D utility range for all models estimated in Table 2. Table 3 indicates that the estimation techniques of tobit and CLAD do not clearly improve the accuracy of the generated predictions as MAE and MSE are not reduced.

The root mean squared error, mean error and mean absolute error calculated from leave-one-out cross-validation were used to assess prediction accuracy.

Root-mean-square error, mean square error, absolute square error, mean error, root-mean-square standardized error, measured values versus predicted values were used for cross-validation.

Root mean square error, mean absolute error, mean absolute relative error and determination coefficient statistics were employed for the evaluation accuracy of each model.

The following performance metrics were used in the benchmark process: Mean error (GB) Mean error Median error (GB) Median error Mean absolute error (GB) Mean absolute percentage error Mean runtime Median runtime.

The mean percentage error (mean absolute error/ maximum experimental force) for these predictions was 7±3%.

Data as mean (mean error standard) or median (percentiles 25-75).