Sentence examples for maximum predictive power from inspiring English sources

Note that we do not specify a particular measure of sensitivity to be used when identifying measurables with maximum predictive power, as such considerations are ordinarily application-dependent (see [39] for some useful specifications).

The maximum predictive power of expression for copper sulfate is 58% considering the 10 most predictive transcripts, while the maximum predictive power of genotype is 93% considering only the single most linked genetic marker.

The maximum predictive power of expression for tetrachloroisophthalonitrile is 65% considering the 500 most predictive transcripts, while the maximum predictive power of genotype is 90% considering only the single most strongly linked genetic marker.

The maximum predictive accuracy of expression for pentachlorophenol is 69% considering the 500 most predictive transcripts, while the maximum predictive power of genotype for it is 90% considering the single most linked genetic marker.

Consequently, these MAQC-II gene expression signatures offer a unique opportunity to develop novel meta-analysis strategies that yield a minimum set of features with maximum predictive power.

The combination of two variables yielded the maximum predictive power with a mean AUC of 0.961 on the model set and 0.801 on the test set.

For various clinical endpoints, the maximum predictive powers of different microarray-based models are limited by the correlation between endpoint and gene expression profile of disease samples as indicated by the consistency degree score.

However, several goals to ensure the maximum reliability at predictive power of extinction risk were achieved in our modelling by incorporating uncertainty in parameter estimates and stochasticity in population dynamics [24], [25].

Minimum support and confidence are fixed to the maximum values in order to obtain the highest predictive power rules for each discretization level (or combination of levels).

To simplify this model and find the features with the most predictive power we then used MAXR (Maximum R Improvement) selection method, with parameter STOP = 3, to determine the best 3 variable model for predicting p63 occupancy.

Though maximum temperature performed well in predicting HFMD incidence, inclusion of minimum temperature could strengthen the predictive power of the model.