In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
The availability of a huge mass of textual data in electronic format has increased the need for fast and accurate techniques for textual data processing. Machine learning and stat...
Overall performance of the data mining process depends not just on the value of the induced knowledge but also on various costs of the process itself such as the cost of acquiring...