Selection of Relevant Features in Machine Learning.

In this paper, we review the problem of selecting relevant features for use in machine learning.We describe this problem in terms of heuristic search through a space of feature sets, and we identify four dimensions along which approaches to the problem can vary.We consider recent work on feature selection in terms of this framework, then close with some challenges for future work in the area. The Problem of IrrelevantFeatures