The project team identified reasons for Airbnb’s property churn in Washington using machine learning models—Logistic Regression, Decision Tree, Random Forest, and Gradient Boosting. The Random Forest model with a threshold of 0.12 worked better than other models (Accuracy = 0.75, Sensitivity = 0.73, Specificity = 0.76).
The presentation slides are available here.
