Design Choices and Theoretical Issues for Relative Feature Importance, a Metric for Nonparametric Discriminatory Power

摘要

We have developed relative feature Importance (RF1), a metric for the classifier-independent ranking of features. Previously, we have shown the metric to rank accurately features for a wide variety of artificial and natural problems, for both two-class and multi-class problems. In this paper, we present the design of the metric, including both theoretical considerations and statistical analysis of the possible components.