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Chapter 17: Relational Learning and Probabilistic Reasoning

Chapter 17: Relational Learning and Probabilistic Reasoning

pp. 731-764

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, University of British Columbia, Vancouver, , University of British Columbia, Vancouver
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Summary

In the machine learning and probabilistic models presented in earlier chapters, the world is made up of features and random variables. As Pinker points out, we generally reason about things. Things are not features or random variables; it doesn’t make sense to talk about the probability of an individual animal, but you could reason about the probability that it is sick, based on its symptoms.

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