Information gain is a metric used to measure the effectiveness of an attribute in classifying data. It quantifies the reduction in uncertainty about the target variable after observing a particular attribute, helping to determine which feature provides the most valuable information for decision-making. This concept is crucial in constructing decision trees, as it guides the selection of the best splits at each node.
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