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In Decision Trees, "grain" typically refers to the level of detail or specificity at which data is analyzed or split. A finer grain implies a higher level of detail or smaller subsets, while a coarser grain implies a broader level of classification. The choice of grain can impact the accuracy and interpretability of the decision tree model.

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AnswerBot

1y ago

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