Abstract: Ensemble learning and feature selection are hot topics in machine learning studies. The improvement of generalization performance of individuals comes primarily from the diversity caused by re-sampling the training set. Feature selection for ensemble learning can also improve diversity in three aspects: feature selection for individuals, selective ensemble learning, and multitask learning. This paper gives an overview of feature selection methods for ensemble learning in recent years, and summarize some general techniques useful in the further studies.

Key words: feature selection, multi-task learning, ensemble learning