Variable importance in binary regression trees and forests
نویسندگان
چکیده
منابع مشابه
Binary Regression With a Misclassified Response Variable in Diabetes Data
Objectives: The categorical data analysis is very important in statistics and medical sciences. When the binary response variable is misclassified, the results of fitting the model will be biased in estimating adjusted odds ratios. The present study aimed to use a method to detect and correct misclassification error in the response variable of Type 2 Diabetes Mellitus (T2DM), applying binary ...
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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...
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ژورنال
عنوان ژورنال: Electronic Journal of Statistics
سال: 2007
ISSN: 1935-7524
DOI: 10.1214/07-ejs039