Sentence examples for sets of threshold from inspiring English sources

Multiple threshold level values are determined by exhaustively searching through all sets of threshold levels for the given number of classes (K) in to which the image needs to be divided to find the combination that gives the minimum within class variance (or maximum inter-class variance).

The three sets of threshold levels for citation counts, co-citation counts, and co-citation coefficients were (12, 2, 15), (13, 3, 15), and (15, 3, 15), respectively.

The source of date was unchanged and the three sets of threshold levels for citation counts, co-citation counts, and co-citation coefficients were (40, 3, 20), (42, 4, 20), and (45, 5, 20), respectively.

In CiteSpace III, we specified the range of years to be analyzed, the length of time slices within the time interval, and three sets of threshold levels for citation counts, co-citation counts, and co-citation coefficients.

Figure  1 shows the four item-person maps, one for each domain, depicting the person measures (upper panel) and sets of threshold parameters (represented by the numbers 1, 2, 3 for each item in the lower panel) jointly positioned on the same 'logit' continuum ranging from −10 to 10 using the pooled data.

Figures  1, 2 and 3 are the item-person maps for the Symptom, Activity and Impact domains depicting the estimates of person measure (the left panel) and sets of threshold parameter estimates of item difficulty (the right panel) on the same "logit" scale.

We show that both sets of thresholds converge to nearly identical thresholds for rate adaptation in the same scenario.

These findings mirror the previous conclusions that are drawn from Fig. 4 showing that the performance of these three sets of thresholds are similar.

It is to be noted from Table 2 that for each image, different sets of thresholds are obtained to fix the width of the kernel.

Since these two cases are complementary, two different sets of thresholds for a specific HO triggering event can be defined in the network.

We use two sets of thresholds to compute in silico hybridization expectations.