郝建柏, 陈贤富, 黄双福, 杨俊. 一种基于模糊近邻标签传递的半监督分类算法[J]. 微电子学与计算机, 2010, 27(2): 30-33.
引用本文: 郝建柏, 陈贤富, 黄双福, 杨俊. 一种基于模糊近邻标签传递的半监督分类算法[J]. 微电子学与计算机, 2010, 27(2): 30-33.
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HAO Jian-bo, CHEN Xian-fu, HUANG Shuang-fu, YANG Jun. Semi-supervised Classification Algorithm Using Fuzzy Nearest Neighborhood Label Propagation[J]. Microelectronics & Computer, 2010, 27(2): 30-33.
Citation: HAO Jian-bo, CHEN Xian-fu, HUANG Shuang-fu, YANG Jun. Semi-supervised Classification Algorithm Using Fuzzy Nearest Neighborhood Label Propagation[J]. Microelectronics & Computer, 2010, 27(2): 30-33.
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一种基于模糊近邻标签传递的半监督分类算法

Semi-supervised Classification Algorithm Using Fuzzy Nearest Neighborhood Label Propagation

    摘要
  • 摘要: 提出了样本分布无关, 模型简单, 单控制参数的模糊近邻标签传递算法.该算法依据样本与其k个近邻的模糊相似性连接, 使类别标签从标签数据向未标签数据传递, 实现未标签数据的分类.最后, 通过人工合成数据和UCI数据集中数据的分类实验验证了该算法的简单有效性.

     

    Abstract: A Fuzzy Nearest Neighborhood Label Propagation algorithm (FNNLP) is proposed, which is sample distribution independent and is simple with only one parameter.Based on the similarity connections of the k nearest data, FNNLP classifies the unlabeled data by making the labels propagate from labeled data to unlabeled ones.Finally, two promising experiment results of synthesized data and UCI dataset classifications verify the simplicity and effectiveness of FNNLP.

     

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