基于主成份分析的Bagging集成学习方法机器学习中数据集的冗余特征会影响学习器的泛化能力，一些流

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机器学习中数据集的冗余特征会影响学习器的泛化能力，一些流行方法如支持向量机和集成学习也难免于此．研究了利用主成份分析进行特征变换对Bagging集成学习算法的影响，提出一种称为PCA—Bagging的算法，并与其它算法比如单个支持向量机

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