Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction
In this paper, a new discriminant analysis for feature extraction is derived from the perspective of least squares regression. To obtain great discriminative power between classes, all the data points in each class are expected to be regressed to a single vector, and the basic task is to find a tran...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/105687 http://hdl.handle.net/10220/17576 http://dx.doi.org/10.1016/j.patrec.2011.11.028 |