We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate...

In this paper, we develop a decision-theoretic frameworkfor evaluating data mining systems, which employ classification methods, in terms of their utility in decision-making. The decision-theoretic model provides an economic perspective on the value of â extracted knowledge,â in terms of its...

This project develops and applies a cost-benefit analytic framework to evaluate a specific policy option facing the state of Maryland: To operate an early release program for adult inmates within a therapeutic boot camp facility, or a traditional prison that also emphasizes treatment. Drawing on...