| 核扩展判定及核扩展方法 |
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| 引用本文： | 郑逢德,张鸿宾.核扩展判定及核扩展方法[J].北京工业大学学报,2010,36(4). |
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| 作者姓名： | 郑逢德 张鸿宾 |
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| 作者单位： | 北京工业大学计算机学院,北京,100124;北京工业大学计算机学院,北京,100124 |
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| 基金项目： | 国家自然科学基金资助项目(60775011) |
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| 摘 要： | 给出一种判定模式识别算法能否核扩展的方法,该方法具有不被算法具体形式所限制的优点.传统核扩展方法是通过将输入数据映射到特征空间,然后在特征空间运行原始算法,得到相应的核方法.给出另外一种核扩展策略,与传统核扩展方法具有等价性.分析及试验过程都表明,本文的核扩展方法具有可行性.
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| 关 键 词： | 机器学习 模式识别 核方法 核扩展 KPCA |
The Condition of Kernelizing an Algorithm and Kernelizing Methods |
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| ZHENG Feng-de,ZHANG Hong-bin.The Condition of Kernelizing an Algorithm and Kernelizing Methods[J].Journal of Beijing Polytechnic University,2010,36(4). |
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| Authors: | ZHENG Feng-de ZHANG Hong-bin |
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| Affiliation: | College of Computer Science;Beijing University of Technology;Beijing 100124;China |
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| Abstract: | To kernelize an algorithm,there are two key points.That is,whether the algorithm can be kernelized and how to kernelize the algorithm if it can be kernelized.Generally it needs many mathematic skills to determine whether an algorithm can be kernelized.This paper provides a new determining condition for kernelization of algorithms.It has the advantage that it is not limited by the specific form of the algorithm.Traditional kernelizing methods are obtained through mapping the input data to the feature space a... |
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| Keywords: | machine learning pattern recognition kernel methods kernelization KPCA |
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