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A supervised learning technique must be chosen that estimates a set of weights w for the cost function such that for the resulting predictions the difference between the predicted labels and the true labels y is globally minimized.
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The data only weakly supported these predictions: the differences were seen, but were not statistically significant.
Although by each measure the positive predictions show higher conservation than the negative predictions, the differences are small and for the most part not statistically significant.
For the external validation data set, mean predicted total ICU stay was 11.58 days and mean observed ICU stay was 11.99 days, a difference of 9.7 hours (p < 0.001); using the day 1 prediction the difference between observed and predicted ICU stay was 149.3 hours (p < 0.001).
Although the trend showed the prediction, the difference was not significant (recessive: two protein interactions [median]; nonrecessive: one protein interactions [median]; P = 0.22, Mann Whitney test), possibly due to the relatively smaller sample size (fig. 7 B ).
Consistent with our prediction, the difference score (% trials correct in direct gaze condition minus % trials correct in the averted gaze condition) was significantly different in the two groups (p = .008, Mann–Whitney U test; Figure 1b).
Results of forward predictions from geomagnetic field models are "predictions," and the difference between observations and predictions [or, in other words, the observations reduced by the model(s)] is named "residuals".
The 2010 annual mean PfPR2 10 predictions were associated with higher coefficients of variation compared with the maximum mean PfPR2 10 predictions, although the difference was moderate (figure 2C,D).
In the 3C region, the observed Ka and Ka/Ks values were lower than the predictions, but the difference was insignificant.
Predictions about the difference in booth coverage between CMC and Non-CMC areas (adjusted based on the model estimates in Table 4) are shown in Table 5.
Table 7 displays the adjusted predictions about the difference in conversion of X houses to P between CMC and Non-CMC areas (based on the model estimates in Table 6).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com