Information Gain
A concept from information theory that measures the amount of information obtained. In decision-making it often refers to the contribution of choosing an action toward reducing uncertainty about the optimal action, and it is equivalent to an optimization problem over mutual information or entropy, which is usually computationally complex.
Timeline (last 90 days)
JevForest weights the proposals from different trees according to global training information gain, so features with higher information gain receive greater weight in voting.
Information gain—the new, non-redundant facts or reasoning basis that a piece of content contributes relative to the existing context—is the core judgment dimension of decision-based retrieval.
Agents should prioritize asking questions that yield the greatest information gain, rather than asking about every unknown.
Information gain is a core concept in information theory, originating from Claude Shannon's information entropy theory.
All Facts (4)
JevForest weights the proposals from different trees according to global training information gain, so features with higher information gain receive greater weight in voting.
50%UnverifiedInformation gain—the new, non-redundant facts or reasoning basis that a piece of content contributes relative to the existing context—is the core judgment dimension of decision-based retrieval.
50%UnverifiedAgents should prioritize asking questions that yield the greatest information gain, rather than asking about every unknown.
50%UnverifiedInformation gain is a core concept in information theory, originating from Claude Shannon's information entropy theory.
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