Learning from labeled and unlabeled data with label propagation
Learning from labeled and unlabeled data with label propagation
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发表时间：
2002-09
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通讯作者：
Xiaojin Zhu;Zoubin Ghahramani
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作者：
Xiaojin Zhu;Zoubin Ghahramani
我们研究了未标记的数据来帮助分类中的数据，我们提出了一种简单的迭代算法，标签传播，以通过数据集沿数据集沿着高密度区域进行传播。连接其他几种算法。特征选择。
We investigate the use of unlabeled data to help labeled data in classification. We propose a simple iterative algorithm, label propagation, to propagate labels through the dataset along high density areas defined by unlabeled data. We analyze the algorithm, show its solution, and its connection to several other algorithms. We also show how to learn parameters by minimum spanning tree heuristic and entropy minimization, and the algorithm’s ability to perform feature selection. Experiment results are promising.