Sentence examples for mean random performances from inspiring English sources

Chalhoub-Deville calls for "a shift from traditional examinations of the construct in terms of response consistency, to investigations that systematically explore inconsistent (which does not mean random) performances across contexts" (Chalhoub-Deville 2003, p. 378).

We find that this mean random performance sometimes infects very few nodes beyond the seeding budget (b) (plotted in yellow), despite the fact that (b) is sufficient to cause a complete cascade in both (G) and (G') (in this section).

Notably, these budgets are very small for both (text {OAS}_{text {mg}}) and (text {OAS}_{text {tg}}): the horizontal lines that plot seeding budget (b) (yellow) and mean random performance (red) in each of Figs. 12 and 13 almost perfectly coincide.

We note that the false negative rate at which the 10th 90th-percentile 10th 90th-percentiledes the mean random seedintervalormance seems to increase at larger infirston thresholds.

In Fig.  2, for infection threshold (tau =0.4), (p_{text {neg}}=0.45) is the lowest false negative rate for which the 10th 90th-percentile 10th 90th-percentileerformance containtervalmean random-seeding performance (shown in red).

Mean random-seeding performance is shown in red Fig. 18 Increasing link-prediction error under linear threshold model: (text {OAS}_{text {tg}}) in scale-free network.

Mean random-seeding performance is shown in red Fig. 20 Increasing link-prediction error under linear threshold model: (text {OAS}_{text {tg}}) in Spanish email network (1133 nodes).

Figure 1 illustrates this point by comparing greedy seed selection (assuming perfect link information) and mean random-seeding performance across all possible budgets in a 100-node network.

Mean random-seeding performance is shown in red Fig. 16 Increasing link-prediction error under linear threshold model: (text {OAS}_{text {tg}}) in small-world network.

Mean random-seeding performance is shown in red Fig. 22 Increasing link-prediction error under linear threshold model: (text {OAS}_{text {tg}}) in UCI messenger-app network (1281 nodes).

This was repeated 500 times and averaged to get the mean random-control performance score.