Sentence examples for average squared error from inspiring English sources

Aside from some of the small high frequency structures, the estimated MSE is appears similar to the average squared error.

Simulation studies demonstrate that our LPM is competitive with alternatives, in the sense of yielding both smaller sample mean average squared error and better visual performance.

(a) Noisy image, (b) non-aggregated CAWF image estimate, (c) CAWF estimate of MSE, (hat {J}_{i}), and (d) average squared error over 100 noise realizations.

The learning rate and momentum for network training were set respectively to 0.25 and 0.9 and the models were run until a minimum average squared error < 0.063 was obtained.

The optimal SAM combining model combined two BRANN member models and improved upon them in terms of average squared errors by 14.6% and 18.1% respectively.

The best performing algorithm used a response mapping method and predicted the mean EQ-5D with accuracy with an average root mean squared error of 0.17 (Standard Deviation; 0.22).

Area-based models were accurate for all structural attributes, with cross-validated average root mean squared error ranging from ∼3.4 to ∼13.4 in the best modeling case.

We show that averaged squared error (ASE) is a good approximation of MISE; however, this is not the case for a cross-validation criterion.

In this study, the Gaussian Kernel [32] will be used for the estimation of link quality results and a smoothing parameter h, usually referred to as bandwidth, will be chosen using averaged squared error (ASE) in order to prevent under or over fitted estimations and guarantee the quality of the estimation.

Root mean squared (RMS) errors were calculated by subtracting the predicted values from the corresponding observed values, squaring them, and then taking the square root of the averaged squared errors.

Rather than keeping only the much smaller sample from each group of interest, we then suggest to use an extension of the Minimum Averaged Mean Squared Error (MAMSE) weights of Plante (2008, 2009a, b) to borrow strength adaptively from the other groups.