When training classifiers, presence of noise can severely harm their performance. In this paper, we focus on “non-class” attribute noise and we consider how a frequent fault-t...
We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
When using the computer, each user has some notion that "these applications are important" at a given point in time. We term this subset of applications that the user va...
Joshua M. Hailpern, Nicholas Jitkoff, Joseph Subid...
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
In this paper, we examine how to improve the precision and recall of document clustering by utilizing meta-data. We use meta-data through NewsML tags to assist clustering and show...