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MATHEMATICS
Information Theory
Information Gain
Information gain reveals how much uncertainty drops when new data is observed, guiding smarter decisions
7 Feb 2026
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What does information gain primarily measure in the context of decision trees?
The total number of features in the dataset
The increase in randomness after observing a new variable
The reduction in uncertainty or entropy after splitting on a feature
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MATHEMATICS
Information Theory
Information Gain
Information gain measures how much a feature reduces uncertainty in decision trees
4 Feb 2026
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How does information gain help in constructing decision trees for classification?
By selecting the feature that maximizes the reduction in entropy, thus best separating the classes at each node.
By choosing the feature with the highest number of unique values regardless of class distribution.
By minimizing the total number of features used in the tree without considering class separation.
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