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Variable selection using Mean Decrease Accuracy and Mean Decrease Gini based on Random Forest

Published in 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS) • Aug 1, 2016
NobleIDNI8P08W68R82S54
Authors:
Hong Han
,
Xiaoling Guo
,
Yu Hua

Abstract

Variable selection is very important for interpretation and prediction, especially for high dimensional datasets. In this paper, a new method is proposed based on Random Forest (RF) to select variables using Mean Decrease Accuracy (MDA) and Mean Decrease Gini (MDG). We also use dichotomy method to s...

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