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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhe Wang Songcan Chen Zhisong Pan Xuelei Ni |
| Copyright Year | 2009 |
| Abstract | Matrix-pattern-oriented Ho-Kashyap classifier has been demonstrated to have a superior classification performance to its vector classifier. However, it is found that the matrixized classifier takes a large computational complexity for convergence in some cases. To overcome the disadvantage, this paper introduces the early stopping technique into the matrixized Ho-Kashyap classifier and presents a Matrix-pattern-oriented Ho-Kashyap classifier with Early Stopping named MatHKES. The presented MatHKES adopts early stopping as a new regularization technique instead of adding a regularization parameter in the criterion. The proposed algorithm achieves: 1) a less running time; 2) a competitive or better classification performance; 3) an avoidance of over fitting in training. |
| Starting Page | 689 |
| Ending Page | 693 |
| File Size | 263632 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780769535074 |
| DOI | 10.1109/CSIE.2009.8 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-03-31 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer science Automation Space technology Programmable logic arrays Feature extraction Linear discriminant analysis Computational complexity Principal component analysis Automotive engineering Information systems |
| Content Type | Text |
| Resource Type | Article |
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