In multiple-instance learning, training samples are bags which are composed of multiple instances, and the bags are labeled but instances are not. The purpose of learning is to predict the labels of new bags.
在多示例学习中,训练样本是由多个示例组成的包,包是有概念标记的,但示例本身却没有概念标记,学习的目的是预测新包的类别。
参考来源 - 多样性密度学习算法的研究与应用·2,447,543篇论文数据,部分数据来源于NoteExpress
以上来源于: WordNet
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