The phrase "a robust prediction" is correct and usable in written English.
You can use it when discussing forecasts or estimations that are strong, reliable, and well-supported by data or analysis.
Example: "Based on the current trends and data analysis, we can make a robust prediction about the market's future performance."
Alternatives: "a strong forecast" or "a solid estimation."
MB's predictive accuracy (AUC = .75) does not support a robust prediction from early information collected.
For belowground biomass (BGB) a model using only DBH can provide a robust prediction (BGB = 0.207DBH1.668).
To do this, SVR was introduced as a robust prediction procedure to test note taking activity metrics.
The internal (Q2LOO = 0.81, n = 26) and external validation (Q2ext = 0.82, n = 8) indicates a robust prediction for kapp.
Using longitudinal data on bilateral flows between the EU-8 and EU-14, we estimate a robust prediction model that exhibits desirable properties.
The integrated assessment of these changes requires a robust prediction of the potential future characteristics of soil temperature and moisture based on scale-appropriate, process-oriented models.
Note the consistent decrease in SD when AUC and accuracy measures of combinations of engines are derived, this means that an engine that is a resultant of a combination of the three engines provides a more robust prediction.
We present a novel approach to apply machine learning techniques to build a more robust prediction model for band-gap energies (BG-E) of chalcopyrites, a class of materials for energy applications in the fields of solar energy, photocatalysis, and thermoelectrics.
Most important, our prediction system makes use of the fact that it employs three different highly optimized individual systems to provide a more robust prediction, i.e. one with a smaller variance in prediction accuracy and AUC scores, allowing us to gain further insight in the treatment outcome relationship as this study demonstrates.
This result indicates that each latent graph provides prediction knowledge from a specific aspect, and their combination leads to a more robust prediction.
The ensemble modelling approach, however, gives a much robust prediction on error bounds.
