Use R to develop two data-driven models for predicting customer churn. -- 2

The first model is logistic regression, and the second model is decision tree. The target/response variable is Attrition and the evaluation metric is accuracy

1. Describe and explain both models (i.e., methodology) in a short paragraph.
2. Show the key stages of the process of how you implement both models in R.
3. Select the best model and then discuss in detail and summarise the business insights provided. For example, which variables/features are important in prediction? What types of customers are more likely to churn? What do you think might be the reasons behind the findings? Your analysis needs to be reasonable, and you could include some business theories or evidence to justify your statements along with the empirical findings from the provided data.