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If one changes the combination of earnings predictors and uses a subset of predictors, sample size increases by only nine, which frees the concern of having a smaller sample size in exchange for having more predictors.
The random forest algorithm fits many classification trees to a data set using a subset of predictors and a bootstrap sample of the data, then combines the results (Prasad et al. 2006; Cutler et al. 2007).
Let (mathcal {M}_{2}) denote a subset of predictors dictating the features h 2,k, k=0,1, and let (widehat {theta }_{2}^{(ell)}(mathcal {M}_{2})) denote the coefficients obtained by applying step (Q1) of the Q-learning algorithm with predictors (mathcal {M}_{2}) to the ℓth imputed dataset.
Let (mathcal {M}_{1}) denotes a subset of predictors dictating h 1,k, k=0,1,2, and let (widehat {theta }_{1}^{(ell)}(mathcal {M}_{1}, mathcal {M}_{2})) denote the coefficients estimated in step (Q3) of the Q-learning algorithm using predictors (mathcal {M}_{1}) and predicted outcomes (widehat {Y}_{i}^{(ell)}(mathcal {M}_{2}),i=11,ldots, n).
Multiple linear regression and hierarchical partitioning [42] identified a subset of predictors repeatedly explaining most of the variance of compound-specific mass transfer in individual flumes.
An important property of RR is that it cannot select a subset of predictors (e.g., SNPs).
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This paper adopts a Bayesian approach to simultaneously learn both an optimal nonlinear classifier and a subset of predictor variables (or features) that are most relevant to the classification task.
After the LR model has been built using a forward stepwise selection procedure for the choice of a subset of predictor variables x i (i = 1, 2,..., d), each continuous predictor is categorized using a locally weighted scatterplot procedure to subjectively identify cut-off points on the basis of training data.
Starting from an initial dataset of 65 environmental predictors (step a), a subset of 16 predictors was selected (step b) and classified into four groups that reflect different types of environmental factors (see below).
Models using only a subset of biophysical predictors (AET, Deficit, slope position and steepness, and solar radiation) explained 55% of the Rim fire and 58% of the maximum fire burn severity of previous fires.
Find a subset of "good" predictors that show fairly strong (univariate) correlation with the class labels, using all of the samples except those in fold k.
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