Challenge 23: Modeling Churn Predictions - Part 1 A telecom company wants you to predict which customers are going to churn (that is, are going to cancel their contracts) based on attributes of their accounts. To this end, you are expected to use a decision tree classifier. The company gives you two datasets (training and test), both with many attributes and the class ‘Churn’ to be predicted (value 0 corresponds to customers that do not churn, and 1 corresponds to those who do). You should train the decision tree classifier with the training data, and assess its quality over the test data (calculate the accuracy, precision, recall, and confusion matrix for example).