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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