8.1 Practical Machine Learning with R Churn Analysis (unbalanced)

This workflow repeats the Churn Analysis from the textbook Practical Machine Learning with R (https:\\ai.lange-analytics.com). We are using unbalanced data for a churn analysis. "Unbalanced" means that one class (customers who did not churned) contains significantly more observations than the other class (customers who churned). Check the Value Count Node to see how imbalanced the data are. Consequently, the model focuses too much on the majority class. Check the Sensitivity and Specificity in the Scorer to see the problem.

External resources

• Contact the author
• Another workflow in this space uses SMOTE to balance the data
• Open the related R analysis in RStudio
• Practical Machine Learning with R (Chapter 8)