Airbnb Booking Prices

Requirements Clarification & Assessment

1. Understanding the Problem Statement:

   • The task is to develop a model to forecast Airbnb booking prices.
   • We need to choose between linear regression and random forest regression.

2. Data Assessment:

   • Identify the features available in the dataset, such as location, seasonality, number of bedrooms and bathrooms, type of accommodation, and external demand factors.
   • Assess the size of the dataset and the nature of the features (categorical vs. continuous).

3. Objective:

   • Determine the model that provides the most accurate prediction of booking prices.
   • Consider the interpretability of the model results.

4. Constraints:

   • Availability of computational resources.
   • Time constraints for model training and evaluation.

5. Performance Metrics:

   • Use metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared for model evaluation.