Project Information:
- Languages/Tools: R
- Project Date: Feb 2023 - May 2023
- Github URL: Click Here
Description:
Gathered and preprocessed a large dataset of NYC Airbnb listings, including features such as location, property type, amenities, reviews, and prices.
Cleaned and preprocessed the dataset by handling missing values, outlier detection, and data normalization to ensure high-quality input for the model.
Explored various regression algorithms and selected the most suitable model based on performance metrics and domain knowledge.
Results:
We identified key factors influencing prices, built a linear regression model, and achieved a reasonable prediction accuracy with an RMSE of about $48.74. These insights empower hosts and guests to make informed pricing and booking decisions. However, considering potential external factors not in the dataset could further enhance the model's accuracy and applicability.