Understanding churn modeling using XAI techniques
Now that you have an idea of the ELI5, LIME, and SHAP techniques, let’s use them on a real-life problem. For the purpose of demonstration, we will consider the problem of churn modeling.
Churn modeling is a type of predictive modeling used to identify customers who are likely to stop using a company’s products or services, also known as churning. Churn modeling is commonly used in industries such as telecommunications, financial services, and e-commerce, where customer retention is an important factor for business success.
Churn modeling typically involves building a predictive model using ML or other statistical techniques to identify the factors that are most likely to contribute to customer churn. The model is trained on data covering past customers, including information about their demographics, usage patterns, and churn status (that is, whether they churned or not). The model is then used to make predictions...