Secondly, having chart review data from only teaching hospitals might generate a non-random sample, as it might have fewer healthy patients than a sample that included patients from non-teaching hospitals.
Fuzzy weighting, which is designed to reduce the effects of outliers for batch classification problems, might generate unreasonable membership grades especially for the samples following an input outlier, when incorporated into online classification algorithms directly.
For example, OxyR regulon members were concentrated in cluster 7, but were also part of clusters 5 and 8. Collecting samples more frequently, over a longer time series and with more biological replicates might generate tighter groupings.
A wider sample, including patients from other specialities or, indeed, members of the public (who are all potential patients), might generate different views.
Honesty might generate trust.
These might generate 20percentt of the building's electricity.
It just might generate the groundswell of public support needed.
A hit movie might generate several hundred thousand sales.
Femtocells might generate significant interference to the MUEs.
The unbalanced growth policy might generate income inequality, and this might induce some welfare loss.
