Efficient feature selection method using contribution ratio by random forest

Abstract

In the field of image recognition, a high-dimensional feature vector is often used to construct a classifier. This presents a problem, however, since using a large number of features can slow down training and degrade model readability. To alleviate this problem, sequential backward selection (SBS) has come to be used as a method for selecting an effective… (More)
DOI: 10.1109/FCV.2015.7103746

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