Structured training: a common-sense approach to developing ADP skills for improved job performance

Supervised learning requires a large amount of labeled data but the data labeling process can be expensive and time consuming. Co-training is a semi-supervised learning method that reduces the amount of required labeled data through exploiting the ...

Multi-label learning aims at assigning a set of appropriate labels to multi-label samples. Although it has been successfully applied in various domains in recent years, most multi-label learning methods require sufficient labeled training samples, ...

In many practical data mining applications, such as Web page classification, unlabeled training examples are readily available, but labeled ones are fairly expensive to obtain. Therefore, semi-supervised learning algorithms such as co-training have ...