It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
We reduce email overload by addressing the problem of waiting for a reply to one’s email. We predict whether sent and received emails necessitate a reply, enabling the user to b...
We use automatically extracted acoustic features to detect speech which is generated under stress, achieving 76.24% accuracy with a binary logistic regression. Our data are task-o...
Matthew Frampton, Sandeep Sripada, Ricardo Augusto...
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...