Sentence examples for in prediction that from inspiring English sources

It's one thing to engage in prediction that flows from analysis: which side is most likely to win? It's quite another to let readers in on the fact that one side's argument is so manifestly weak that it doesn't deserve to win.

This last example shows the advantage of using two approaches for the AD (instead of a global one only) in addition to the confidence level in prediction that allows the user to make rational judgement about prediction reliability.

Thus, boosting produces classifiers that are better in prediction that the current ensemble.

As we previously showed, several clinicopathologic parameters that are easily and routinely measured, provided excellent predictive power for outcome in HCC [ 10] and result in predictions that were readily applicable to clinical practice.

There was considerable between-site variation in predictions that reflected variation in site productivity.

This paper introduces the fuzzyness of the class boundaries which result in predictions that may belong to more classes.

Our explanation for this is: a small numbers of Gaussian processes are not able to capture or describe all the motion possibilities for actions, which results in predictions that are not accurate.

In all these systems, predictions based on animal movements (rather than home-ranges) and/or habitat use may be more adequate, and may result in predictions that are well-described by one-dimensional curves ([12], but see [13]).

Screening with the 'Sugar transferases' and 'UDP-glycosyltransferases' HMMs in contrast resulted in predictions that were quite GT-specific, as indeed approximately 50% of the originally obtained predictions also contain a GT-like fold.

G BASE tended to inflate the variance of genetic merit of individuals, while reweighted G RR and G BL resulted in predictions that were the least biased, with G SM showing intermediate performance.

However, a study by Willis and colleagues [ 42], using a population pharmacokinetic model based on Bayesian forecasting and adapted for individual pharmacokinetic, demographic, and covariate data, resulted in predictions that were too imprecise.