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Next, classification and regression trees (CART) [ 19] were composed that divided the sample in subgroups as homogeneous as possible with regard to the outcome by selecting the most predictive variables based on minimum prediction error.
Then, considering minimum prediction error, an optimal artificial neural network was designed to predict the relative viscosity of the nano-lubricant.
Finally, the optimum result y is produced with the minimum prediction error [24].
The number of components was determined by cross-validation to have a minimum prediction error.
Beside the Least Squares class of methods, Minimum Prediction Error and Minimum Output Error methods have been investigated as well.
This is achieved by considering a quadratic polynomial relationship between the output and input elements so as to generate the minimum prediction error.
Similar(41)
Minimum mean AIC is related to minimum mean prediction error, where the mean is taken across multiple studies and prespecified models; this should be borne in mind when analyzing a data set from just one study.
The minimum Prediction Residual Error Sum of Squares (PRESS) was 0.824 tested by leave one out cross validation.
Furthermore, it gives better results especially for non-SPR channels compared to the well-known minimum nonlinear prediction error method and the simplified recursive algorithm developed in our previous work.
The performance of receivers employing both optimal and suboptimal front-ends has been assessed by means of minimum mean square prediction error (MMSPE) analysis and bit-error rate (BER) simulations.
The optimal combination of the parameters was found at the values where the minimum mean square prediction error (MSPE) was attained.
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