According to this procedure, an A' value equal to 1.0 represents maximum accuracy; a value of 0.5 indicates chance-level performance.
In this study, we chose 0.5 for PEMG and 0.1 for Pdelta because these values give the maximum accuracy when we used these values for nonclustered epochs (Fig. 3B).
Solberg et al. [ 14] concluded that a density of 800 was not sufficient to achieve the maximum accuracy of genomic breeding values.
This criterion is defined as the maximum accuracy achievable when each value of a feature predicts a different class value.
The reason for this combination is related to the fact that measurements show the maximum accuracy around quarter-wave retardance values (i.e., where the normalized transmission is 50%%) [10, 12].
As shown in Figure 3, the maximum accuracy was achieved when the value of K was equal to 3. Thus, when K was more than 3, the accuracy decreased as K increased.
Assume that (tilde{A}) and (tilde{B}) be two GLRFNs, validity rating of (Apreceq B) is belong to interval ([t_{Apreceq B},1-f_{Apreceq B}]) where (t_{Apreceq B}) minimum accuracy and 1-f_{Apreceq B}}) maximum accuracy and we show with vague value of rank (tilde{A}preceq tilde{B}) with (mathrm{VR}(Apreceq B)) where mathrm{VR}(Apreceq B =[t_{Apreceq B},1-f_{Apreceq B}] (9).
However, when looking at the range of accuracies observed for all 10 cross-validation datasets these values do not exceed the maximum accuracy observed.
Using this metric, the higher accuracy values the better performance of the model tested (maximum around 1).
Finally, when the value of λ is within the range [0.1, 0.9], the differences among the accuracy rates obtained with different values of λ are relatively small, and the decrease in maximum accuracy is just 1.82%.
