| 支持向量机训练算法的比较研究 |
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| 引用本文： | 俞胜益,付燕. 支持向量机训练算法的比较研究[J]. 科技情报开发与经济, 2008, 18(30): 138-140 |
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| 作者姓名： | 俞胜益 付燕 |
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| 作者单位： | 西安科技大学计算机学院,陕西西安,710054 |
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| 摘 要： | 介绍了支持向量机的数学模型,重点论述了两种比较典型的分解算法,即SVMlight和SMO,并对这两种算法的优点和缺点进行了分析和总结。
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| 关 键 词： | 支持向量机 SVMlight SMO |
The Comparative Research on Support Vector Machine Training Algorithm |
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| YU Sheng-yi,FU Yan. The Comparative Research on Support Vector Machine Training Algorithm[J]. Sci-Tech Information Development & Economy, 2008, 18(30): 138-140 |
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| Authors: | YU Sheng-yi FU Yan |
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| Affiliation: | YU Sheng-yi, FU Yan |
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| Abstract: | This paper introduces the mathematical model of support vector machine, expounds two typical decomposition algorithms, SVMlight and SMO, and analyzes and sums up the advantages and disadvantages of these two algorithms. |
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| Keywords: | SVMlighl SMO |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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