The phrase "a large set of predictors" is correct and usable in written English.
It can be used in contexts such as statistics, data analysis, or machine learning when referring to multiple variables that are used to predict an outcome.
Example: "In our study, we analyzed a large set of predictors to determine the factors influencing consumer behavior."
Alternatives: "a significant number of predictors" or "an extensive collection of predictors".
The method is also used in an empirical application to forecast eight key US macroeconomic time series over various horizons, where the components are constructed from a large set of predictors.
Moreover, the algorithm can be easily modified to read in different predictors, and dependent variables, and thus has the potential to be applied to any industrial process involving a large set of predictors.
A large set of predictors, involving many different bodily functions and activities, were included.
Other regularization methods related to RR are able to select a subset of predictors from a large set of predictors.
Because a large set of potential predictors was compared, there was a risk that at least 1 indicator would reach the.05 level of significance purely by chance [ 77].
One plausible reason why researchers choose not to use IPD for external validation is that they want to maximise the data available for model development; this is understandable, especially when faced with a large set of candidate predictors and possible non-linear relationships.
In contrast to other regression approaches, PLS-DA is designed to perform discriminate analyses based on a large set of noisy and collinear predictors X and is therefore suitable for the large number of gait features investigated in the present study.
This is due to the large set of predictors already considered and to the fact that level change across cohort has not been demonstrated before.
In the scoring experiment, a large set of models submitted by the docking predictors is made available to the community to test scoring functions independently of conformation generation algorithms.
The average performance of a predictor over a large set of queries can thus be measured by its Mean Reciprocal Rank (MRR), MRR = 1 n ∑ i = 1 n 1 rank i.
However, the finding should be interpreted with caution, as predictive value is generally overestimated when the model is created and evaluated in the same study population, particularly if the same data were first used to select the strongest genetic predictors out of a large set of genotyped variants [ 73].
