Sentence examples for a correct predictor of from inspiring English sources

When applying the BNN model, no classification errors came out when the probability of diagnosis was higher than 90%, thus allowing us to use this model as a correct predictor of samples with a probability score >90% (p < 0.0001).

By applying the BNN model, no classification errors came out when the probability of diagnosis was higher than 90%, thus allowing us to use this model as a correct predictor of samples with a probability score >90% (p < 0.0001).

It appears that our choice to eat sweet foods either as a replacement or as an addition to other nutrients may be a more correct predictor of whether sweet foods will have an effect on body weight than are mere measurements of total sweet intake.

This can be explained in two ways: either recorded patients characteristics are not the correct predictors of response, or response is not adequately defined (e.g., by FEV1, which is used in most studies).

Example of change on the inferred predictor by using different values for q entropic parameter: (a) distributions that lead to wrong predictor and (b) distributions that lead to correct predictor.

Similar to correct reasoning, attendance was a significant predictor of choosing correct answers for taxa-relatedness questions, while major and year in school were not significant factors.

Thus, it was not surprising that attendance during targeted, active-learning instruction on evolutionary relatedness was a significant predictor of correct taxa-relatedness reasoning.

This suggests that the low gamma35-55 Hz rhythmic circuit tends to engage its principal cells at a specific phase irrespective of trial outcome, while the magnitude of this engagement is a stronger predictor of correct performance.

Contrasting, Suhail [ 15] found that only 20%percentt of Pakistani people were able to identify depression, and even less (5%) were able to identify psychosis from a written vignette, and furthermore that level of education was a predictor of correct identification.

Using the Compound Covariate Prediction Method (CCPM), this predictor set gave a correct classification of PC vs. non-PC with an accuracy of 73%, providing a sensitivity of 71% and a specificity of 75%.

In a naive analysis, a strong positive association could be found between clean hospital floors (predictor variable X3) and a correct assessment of fetal health (response variable Y).