Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can...
Qinbao Song, Martin J. Shepperd, Xiangru Chen, Jun...
As processor architectures have increased their reliance on speculative execution to improve performance, the importance of accurate prediction of what to execute speculatively ha...
In supervised machine learning, the partitioning of the values (also called grouping) of a categorical attribute aims at constructing a new synthetic attribute which keeps the info...
We describe the problem of mining possibilistic set-valued rules in large relational tables containing categorical attributes taking a finite number of values. An example of such a...
Decision tree grafting adds nodes to inferred decision trees. Previous research has demonstrated that appropriate grafting techniques can improve predictive accuracy across a wide ...