In classification and regression trees (CART), it is done by the model itself, based on how dirty it is. Features that are used in CART are thought to be the most important parts of the tool. Some experts said that people should not have to choose features before they build CART. However, some other analysts disagreed and said that, as long as we need to run models, feature selection is still an important step before building a model. Before running CART models, do you think it is important for users to pick out the features they want to use?

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A: Dear Student, The answer to your question is given below -

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A: Answer:

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A: HI THEREI AM ADDING ASNWER BELOWPLEASE GO THROUGH ITTHANK YOU

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A: The Answer is

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Q: Is there a certain modelling approach that should be used, and why was it chosen for a specific…

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