The phrase "a pool of predictors" is correct and usable in written English.
It can be used in contexts related to statistics, machine learning, or data analysis, where multiple variables or features are being considered for prediction.
Example: "In our study, we analyzed a pool of predictors to determine the factors influencing customer satisfaction."
Alternatives: "a set of predictors" or "a collection of predictors".
Unlike traditional regression models, a tree-based method has several attractive properties: it is less sensitive to outliers, it requires no distributional assumption or data transformation, it is adaptable to complicated interactions among a large pool of predictors, the results are visually intuitive, and the prediction rule is easy to follow [ 38, 41].
For this study, a pool of 412 potential predictors was assembled, which included qualitative location classes, elevation, land-surface derivatives (with a wide range of analysis scales), hydrologic indicators, as well as proximal and remote sensing (from multiple sources with a variety of resolutions).
This resulted in a pool of 21 potential predictors: the 6 single variables {x 1,…,x 6}, plus a total of 15 interaction terms {x 12,…,x 56}.
To study the relationship of the caudate DAT concentration with diagnosis independently of the severity of motor disease, we evaluated the caudate DAT concentration using a GLM that included putamen DAT concentration as a covariate in the original pool of predictors.
One of the crucial problems of the classifier ensemble is the so-called combination rule which is responsible for establishing a single decision from the pool of predictors.
Multiple linear regression via the forward-stepwise algorithm (α = 0.05) with SPSS 21.0 was used to reduce the large pool of predictors to a few that were most important in describing needs related to the three dimensions of PD (basic pedagogy, contemporary evolution instruction, and standards-based evolution instruction).
A possible explanation for these results is that RACING INTENSITY acts as a representation of the "healthy horse" effect, making correlated variables such as RACING SPEED not significant when introduced in the same explanatory pool of predictors.
After establishing a benchmark, potentially relevant predictors were identified to populate a pool of candidate independent variables based on a literature review and cognitive theories.
Predictors of neonatal demise were determined from a pool of 24 candidate variables in a univariate analysis.
A pool of blood surrounded her.
