We used the average test-data AUC, which showed that 52 species distribution models were reliable (i.e. accurate and stable, Table S1).
Since it was not feasible to test multiple subjects as in our previous human psychophysical studies, we instead averaged the test data over a larger number of repetitions (240 trials per fragment, except where noted otherwise) from each of the two animals.
Figure 20c shows the normalized absolute average error of test data per normalized forecasting length (h). Figure 20d shows the divergence between test data and network test data.
Each group consisted of three nominally identical specimens, a total of 180 specimens were prepared, and the final result is taken as the average of three test data.
The estimate of accuracy, r (PEV ), when averaged over the test data set, was similar to the empirical accuracy of the group r(cor).
In this case the effect of replacing the above pathway feature with the averaged pathway feature ∑ i ∈ leading edge genes x ~ ij (with appropriate final normalization) allows avoidance of the noise inherent in overly noisy weights w i, as well as denoising by equal averaging of the test data noise terms z ij.
The average NCBM particle size was measured 10 times, and the five closest test data were averaged as the test result.
The average absolute deviation for the test data set was found to be 0.067 J K−1 g−1.
Then, the orthogonal test data of average particle velocity and screening efficiency for 16 cases are analysed by using the direct analysis method.
It must be noted that, although the length of the speech data used for training/development is greater than that of the test data, the average number of occurrences per minute in both sets is similar.
We found that the average sentence length of both test data sets resemble the length of sentences contained in the most relevant biomedical literature sources (table 1).
