AdaBoost Multiple Feature Selection with SVM-based Component Classifiers for Gender and Age Classification
碩士 === 國立清華大學 === 資訊工程學系 === 101 === Although SVM (Support Vector Machine) is a strong classifier that cannot be combined with AdaBoost (Adaptive Boosting) easily, it has been proved to be effective component classifier in AdaBoost. In this paper, we propose AdaBoost multiple feature selection with...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/43144610879415393757 |