A novel relation aware wrapper method for feature selection

Zhaogeng Liu, Jielong Yang, Li Wang, Yi Chang

Abstract: Highlights•We propose a novel wrapper feature selection method ERASE.•ERASE can learn the sample graph and forest-related feature relations simultaneously.•A novel selection strategy is developed based on the forest-related feature relations.•ERASE achieves better performance than 13 baseline methods on 9 datasets.