Abstract
The Bhattacharyya distance provides a valuable information in determining the effectiveness of a feature set and has been used as separability measure for feature selection. Recently, it is shown that it is feasible to predict the classification error accurately using the Bhattacharyya distance. The new formula makes it possible to estimate classification error between two classes within 1-2% margin. In this paper, we propose a new feature extraction method utilizing the result. Initially, we start with an arbitrary feature vector. Assuming that the feature vector is used for classification, we estimate the classification error using the error estimation formula. Then we move the feature vector slightly in the direction so that the estimated classification error is decreased most rapidly. This can be done by taking gradient. Experiments show that the proposed method compare favorably with the conventional methods.
Original language | English |
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Pages (from-to) | 2147-2150 |
Number of pages | 4 |
Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
Volume | 3 |
Publication status | Published - 1997 |
Event | Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - Orlando, FL, USA Duration: 1997 Oct 12 → 1997 Oct 15 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Hardware and Architecture