In classification and regression trees (CART), it is performed by the model itself based on impurity measures. Features that are used in CART are considered the most important ones. Some analysts suggested that users do not have to select features prior to the construction of CART. However, some other analysts disagreed and argued that, as long as we need to run models, feature selection remains a critical step before model construction. Do you agree that feature selection by users before running CART models is important?

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