如果你想使用有监督的学习算法，你需要标记数据。
If you want to use some supervised learning algorithm, you need labeled data.
半监督学习算法同时考虑有标记和无标记数据，能显著提升学习效果。
Semi-supervised learning algorithms, which consider both labeled and unlabeled data, can improve learning effectiveness significantly.
该方法通过几个分类器间协同学习，选出标记可信度比较高的无标记数据，再利用这些数据对已有的分类器作进一步的改进。
This method utilizing co-learning among several classifiers, selects the unlabeled samples which have high confidence, and then refines each classifier with these samples.
该方法通过几个分类器间协同学习，选出标记可信度比较高的无标记数据，再利用这些数据对已有的分类器作进一步的改进。
This method utilizing co-learning among several classifiers, selects the unlabeled samples which have high confidence, and then refines each classifier with these samples.
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