Erratum to: Informative metabolites identification by variable importance analysis based on random variable combination

Random Forest variable importance with missing data

Random Forests are commonly applied for data prediction and interpretation. The latter purpose is supported by variable importance measures that rate the relevance of predictors. Yet existing measures can not be computed when data contains missing values. Possible solutions are given by imputation methods, complete case analysis and a newly suggested importance measure. However, it is unknown t...

Image Restoration by Variable Splitting based on Total Variant Regularizer

The aim of image restoration is to obtain a higher quality desired image from a degraded image. In this strategy, an image inpainting method fills the degraded or lost area of the image by appropriate information. This is performed in such a way so that the obtained image is undistinguishable for a casual person who is unfamiliar with the original image. In this paper, different images are degr...

Computing tolerance interval for binomial random variable

Tolerance interval is a random interval that contains a proportion of the population with a determined confidence level and is applied in many application fields such as reliability and quality control. In this educational paper, we investigate different methods for computing tolerance interval for the binomial random variable using the package Tolerance in statistical software R. 

On the Random Variable

Dependence of Variable Importance in Random Forests on the Shape of the Regressor Space Supplement to “ Variable Importance Assessment in Regression : Linear Regression Versus Random Forest ”

Figure: Averaged normalized importances for X1 from 100 simulated datasets (simulation process described below) for m=1,2,3,4 (left to right) with β1=(4,1,1,0.3) , corr(Xj,Xk)=ρ |j−k| with ρ=−0.9 to 0.9 in steps of 0.1 Grey line: true normalized LMG allocation; Black line: true normalized PMVD allocation : Variable importance (% MSE Reduction) from RF-CART; ×: Variable importance (% MSE Reducti...