Machine Learning
Singapore HDB Resale Price Predictor
A gradient boosted regression model that predicts future resale prices of Singapore HDB flats from historical transaction data.
Overview
Singapore's HDB resale market publishes rich historical transaction data, but pricing a flat still comes down to gut feel for most buyers and sellers. This project trains a gradient boosted regressor on past resale transactions to predict future resale prices, using features like flat type, floor area, remaining lease, and location.
What it covers
- Data cleaning and feature engineering on historical HDB resale transactions
- Gradient boosted regression model training and hyperparameter tuning
- Model evaluation against held-out transaction data
Tech stack
- Python
- Gradient boosted regression (scikit-learn / XGBoost-style modelling)
- SQL for data wrangling