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A Decision Tree classifier is a popular machine learning algorithm used for both classification and regression tasks. It works by splitting the dataset into branches based on feature values, creating a tree-like model. In R, the `rpart` library is commonly used for building Decision Tree models, and visualization can be achieved with the `rpart.plot` package. Here's an example of how to create a Decision Tree classifier, visualize the results, and interpret the outputs. ### Step 1: Install necessary libraries First, ensure that the necessary libraries are installed and loaded. You can ________ ________ ________ ________ _______ ___ _____ _________ _____ ___ _________.
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