Sentence examples for goodness of prediction from inspiring English sources
The quality of the model is R2 = 0.868, Q2 = 0.517 (Figure 2), where R2 is the goodness of fit value and is a measure of how well the model fits to raw data, and Q2 is goodness of prediction and estimates the predictive power of the model.
The quality of each model was determined by the goodness of fit parameter (R) and the goodness of prediction parameter based on the fraction correctly predicted in a 1/7 cross-validation (Q).
OPLS model quality was evaluated based on the parameters R Y (goodness of fitting, i.e., fraction of Y variation modelled by the predictive component) and Q Y (goodness of prediction) as determined through the default leave-1/7th-out cross validation test.
The goodness of prediction and goodness of fit are very good for both regression models.
Q2 describes the goodness of prediction – the fraction of the total variation of the variables that can be predicted by a principal component using cross validation methods.
Best goodness of fit (R2 = 0.94) and goodness of prediction (Q2 = 0.90) values were obtained using particle-size results of the spatial filtering technique.
Several diagnostic statistical tools were implemented for characterization the goodness-of-prediction or predictability of obtained models.
Goodness-of-prediction parameters measure the true predictive ability of a model and are related to the reliability of prediction.
In addition, the goodness-of-prediction criterium (G) are higher than zero indicating that spatial soil properties mapped based on kriging interpolation are more accurate than the catchment average value (classical statistics) for site-specific management decisions.
The quality of continuous models was evaluated using two groups of statistical indices, goodness-of-fit parameters and goodness-of-prediction parameters.
To evaluate the goodness of this prediction, we consider the error measures precision and recall (see Additional file 1 for a general definition of precision and recall).
