Nonparametric Feature Selection Method Based on Local Interclass Structure
- 1 April 1981
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics
- Vol. 11 (4) , 289-296
- https://doi.org/10.1109/tsmc.1981.4308675
Abstract
A nonparametric feature selection method which can be applicable to pattern recognition problems based on mixed features is presented. In the pattern space, each pattern class is represented by multiple subregions according to local interclass structure. Then in each of the subregions, feature selection is performed in a simple nonparametric way. Our feature selection method can select a feature subset based on higher order discriminating information. Some basic properties of our approach are presented theoretically and experimentally.Keywords
This publication has 3 references indexed in Scilit:
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- A Recursive Partitioning Decision Rule for Nonparametric ClassificationIEEE Transactions on Computers, 1977
- Multiclass Pattern Recognition Systems Based on Independent Subrecognition SystemsIEEE Transactions on Systems, Man, and Cybernetics, 1976