Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain.

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THEORETICAL NOTES Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain

Several norms for how people should assess a question’s usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback–Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment, medical diagnosis, and the selection task are s...

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Finding useful questions: on Bayesian diagnosticity, probability, impact, and information gain.

Several norms for how people should assess a question's usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback-Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment, medical diagnosis, and the selection task are s...

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ژورنال

عنوان ژورنال: Psychological Review

سال: 2005

ISSN: 1939-1471,0033-295X

DOI: 10.1037/0033-295x.112.4.979