About this document
Real Estate Project Presentation by sahar is a document available to read on EtoBox.
This project aims to predict property sale prices in Connecticut using historical real estate data from 2001 to 2020, utilizing machine learning algorithms. The dataset consists of approximately 500,000 records with 21 features, and the Random Forest model demonstrated the highest accuracy with an R² of 0.86. Key findings highlight the importance of assessed value in predicting sale prices and the significance of data cleaning and feature selection in model performance.
- Author
- sahar
- Language
- EN