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OALib Journal期刊
ISSN: 2333-9721
费用：99美元
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一种基于多模态模型的随机子空间分类集成算法
, PP. 57-62
Keywords: 多模态,随机子空间,分类器集成
Abstract:
分类是当前机器学习的重要研究内容之一,已取得了一定的进展.现有的文本分类方法大多基于VSM模型,而VSM未能有效地利用隐含在文本中的结构信息.同时,VSM下的样本空间常常是高维的,单一的降维策略可能会丢失有用信息.为改进现有算法的不足,提出了一种基于多模态模型的随机子空间分类集成算法MMRFSEn,有效地利用文本中的结构信息(单词分布位置的均值和标准差),且各基分类器是由随机选择的子空间构建而成.实验结果表明,该方法是有效可行的.
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