We used 10-fold cross-validation to identify the value of the regularization parameter that minimized the average mean-squared error on this held-out test set.
To confirm each supervised comparison, we used 10-fold cross validation to identify the set of genes/miRs/proteins that minimized the average mean-squared error on each testing set.
First, an optimal estimator gain is designed for each sensor by minimizing the mean-squared estimation error covariance.
Based on the event-triggered scheme, an optimal estimator gain is designed by minimizing the mean-squared estimation error covariance, and then a sufficient condition is provided to guarantee the stability of the proposed distributed estimator.
Actually, instead of minimizing the feedback components in the residual signals, the AFC filters are optimized by minimizing the mean-squared error of the overall residual signals (38).
Given the data compensated in the aforementioned steps, we then wish to estimate the clutter voltage of by minimizing the mean-squared error (MSE) as.
In addition, these currents are further smoothed by minimizing the mean-squared magnitude of the surface divergence of the diurnally varying portion of Jeq at mid-latitudes at all local times.
Using z j (i) (j = 0, 1), from (15), the k th user minimum mean squared error (MMSE) receiver for each symbol, wk,j, is obtained by minimizing the mean-squared error criterion w k, j = arg min w E | s k ( 2 i + j ) - w H z j ( i ) | 2, (18).
The lack of repeatability from one analysis to the next is most likely due to the fact that training a NN involves minimizing a mean-squared error function.
The main idea of the Savitzky-Golay filter is to apply a FIR filter such that its coefficients minimize the mean-squared approximation error.
