Comparison of Feature Dimension Reduction Approach for Writer Verification
Dimension reduction is useful approach in data analysis application. In this paper, research is done to test whether the concept of Dimension reduction can be applied to improve writer verification process results. Two approaches have been chosen to be compared which are Features Selection and Feat...
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| Main Authors: | , |
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| Format: | Book Chapter |
| Language: | en |
| Published: |
Springer
2011
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/11938/1/DaEng_Rima_Final.pdf http://eprints.utem.edu.my/id/eprint/11938/ |
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| Summary: | Dimension reduction is useful approach in data analysis application. In this paper, research is done to test whether the concept of Dimension reduction can be applied to improve writer verification process results. Two approaches have been chosen to be compared which are Features Selection and
Feature Transformation, where the comparison is on the way of reducing the dimension of writer handwritten data. Both approaches have slightly difference results in reducing the data and classification accuracy. The objective of this
paper is to observe the differences between both approaches according to the classification accuracy results, by using some classification techniques. |
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