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Document type:
Technical Report 
Author(s):
Marianne Mueller; Romer Rosales; Harlad Steck; Sriram Krishnan; Bharat Rao; Stefan Kramer 
Title:
Data-Efficient Information-Theoretic Test Selection 
Abstract:
Many real-world applications, where data gathering and analysis play a central role, are faced with the fundamental question of how to select variables (to be instantiated or measured) that can efficiently reduce uncertainty. In this paper, we use the concept of conditional mutual information to approach problems involving the selection of variables observations in the area of medical diagnosis. Computing mutual information requires estimates of joint distributions over collections of variables....    »
 
Keywords:
Test Selection; Mutual Information 
Year:
2009 
Year / month:
2009-05-13 00:00:00 
Pages:
13