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The decision tree is a classification model, applied to existing data. If you apply it to new data, for which the class is unknown, you also get a prediction of the class. The assumption is that the new data comes from the similar distribution as the data you used to build your decision tree. In many cases this is a correct assumption and that is why you can use the decision tree for building a predictive model.

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