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In the process of model building, the researcher may be confronted to a pool of predictors of which some might be redundant in nature.
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.
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.
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].
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With these statistical models, predictors are selected from a larger pool of potential predictors which is frequently established prior to model derivation and originates from previous literature or expert recommendations[ 1].
However, these studies have typically relied on routinely collected data, limiting the pool of potential predictors available for study and necessitating crude variable measurement.
The selection of the appropriate loci from a large pool of potential predictors is a concern with any model building approach, including NN.
Recent evidence identifies other variables potentially associated with hip arthroplasty outcomes that were not included in our study, thus potentially limiting the pool of candidate predictor variables.
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}.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com