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Integrating learning from examples into the search for diagnostic policies

Creator:

Oregon State University. Dept. of Computer Science, Bayer-Zubek, Valentina, and Dietterich, Thomas Glen

Abstract:

This paper studies the problem of learning diagnostic policies from training examples. A diagnostic policy is a complete description of the decision-making actions of a diagnostician (i.e., tests followed by a diagnostic decision) for all possible combinations of test results. An optimal diagnostic policy is one that minimizes the expected...

Resource Type:

Research Paper

Full Text:

modeled as a Markov Decision Problem (MDP). An MDP is a mathematical model for describing the interaction

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Integrating learning from examples into the search for diagnostic policies

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