Discussion
Which criterion does information gain use when choosing a test?
Answer: D
Information gain is the entropy before the test minus the expected entropy after it, averaged over the test's possible outcomes. It is the information-theoretic cousin of the value of information, which weights by utility rather than by entropy. Example counts, outcome probabilities and costs enter other criteria. Noting that both quantities are non-negative for the same structural reason connects the two halves of this topic neatly.
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