Enhancing the Airbnb Performance through Price Prediction and Market Segmentation using Machine Learning
Air BnB is a popular online marketplace and hospitality service that allows people to rent or lease short-term lodging accommodations.
The problem is that both hosts looking to rent out their homes and guests looking to purchase are unaware of the market for the properties they are offering.
Host: Difficult to determine a suitable price for the facilities provided
Guest: Desiring the best facilities at the most affordable price
Data-Driven Price Prediction and Market Segmentation so both host and guest know about the price in the market.
This dataset is Airbnb data for the United States. https://www.kaggle.com/datasets/arianazmoudeh/airbnbopendata
The missing values in the data need to be cleaned up so that machine learning modeling can be performed effectively later on.
This is the step i did:
- Dropping columns with too many null values.
- Removing rows with null values for specific columns.
- Deleting duplicate data.
Other outliers are indicating data diversity. However, the 'minimum_nights' column will be reevaluated due to negative values and some in the thousands.
After that, simple data visualization and Exploratory Data Analysis (EDA) were conducted to gain insights from the data.
Two types of machine learning were performed, namely Price Prediction (regression) and Market Clustering.
The goal of price prediction is for the machine to predict an appropriate price based on the facilities offered by the Airbnb unit.
After performing modeling, the best model is Random Forest with a Training RMSE of 103.06 and a Test RMSE of 289.79.
Market Segmentation is performed using K-Means Clustering with a value of K = 6, determined through the elbow method and silhouette analysis.
Then, six types of Airbnb listings with the target variable being "price" will be identified.
Full presentation for this project at:
https://bit.ly/Portfolio_Oktober_2023
https://jacobsakhnini.com/project_airbnb.html https://www.kaggle.com/code/sayanroy729/airbnb-open-data-eda-step-by-step https://www.kaggle.com/code/lxy21495892/airbnb-eda-pygwalker-demo https://www.kaggle.com/code/iuliabunescu23/imb-data-analytics-final-project https://www.kaggle.com/code/kartikexe/airbnb-dataset-eda-and-feature-engineering https://www.kaggle.com/code/abdelrahmanraslan/airbnb-price-prediction-ml https://www.kaggle.com/code/dtbingh/what-makes-a-successful-airbnb-business