Sentence examples for many negative examples from inspiring English sources

For small problems with up to 200 examples, we typically construct four times as many negative examples as in the original (positive) example set, while for larger domains we construct the same number of positive and negative examples.

It was observed that all classifiers worked well when there were many negative examples.

Five times as many negative examples were selected, to account for the greater variety of negative examples (intergenic, exons, introns, non-promoter regulation such as enhancers, insulators, etc).

Because there are many more negative examples (non-binding sites) in the data than positive examples (binding site residue cluster or pocket) it was necessary to randomly select only a subset of the negative data to obtain a balanced dataset.

Datasets with twice as many negative as positive examples were used because they gave slightly better performance than evenly balanced (1 1 ratio) datasets (data not shown).

Importantly, neglect is associated with many negative factors, for example it appears to have a suppressive effect on upper-limb motor recovery (both synergism and strength) especially over the first ten weeks post-stroke (Nijboer et al., 2014).

Before a computer can know or "see" these things itself, it must be shown many confident positive and negative examples (aka ground truth or gold standard data).

Hence, we would expect to find Sp1 binding sites in many of the randomly selected negative examples.

While we have discussed a couple of clear negative examples, there are many ways transitive data relationships help us.

For example, there are many negative results (i.e., Ki-67 is not involved in something) that receive substantial space.

Defining positive and negative examples, which itself has many open problems [ 45], is not necessary.