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

Authors:
Hilary J. Holz;Murray H. Loew
Affiliations:
-;-
Venue:
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Year:
2000

Citing 3
Cited 0

Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
Multi-class classifier-independent feature analysis

Pattern Recognition Letters - special issue on pattern recognition in practice V
A Branch and Bound Algorithm for Feature Subset Selection

IEEE Transactions on Computers

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Abstract

We have developed relative feature importance (RFI), 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.