An efficient algorithm of solving the optimal discriminant vectors
| Autor: | Ming-tian Zhou, Hong-zhou He |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Matrix (mathematics)
Multiple discriminant analysis Discriminant Contextual image classification Computer science business.industry Optimal discriminant analysis Singular value decomposition Pattern recognition Artificial intelligence Linear discriminant analysis business Generalized singular value decomposition |
| Zdroj: | 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE). |
| DOI: | 10.1109/csae.2012.6272811 |
| Popis: | In view of the limitations of traditional uncorrelated Linear Discriminant Analysis (uLDA) of failure with singular within-scatter matrix and computationally expensive in solving the optimal discriminant vectors for a large and high-dimension dataset, an equivalent uLDA to Linear Discriminant Analysis (IDA) and a algorithm of uLDA based on generalized singular value decomposition is proposed to simply the computation and get over the singularity problem. The classification experimental results of four image and text datasets demonstrate the superiority of our algorithmover other traditional algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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