Credits

Website#

This website was built with Material for MkDocs, a theme for MkDocs.

API references#

In this project, we have used various libraries and their API documentations. These include, but are not limited to:

• Scikit-learn
• XGBoost
• TensorFlow and its high-level API Keras
• NumPy
• Scipy
• Plotly Express
• Seaborn
• Matplotlib
• Pandas
• Pandas Profiling
• Python Documentation
• Statsmodels
• OneMap API
• Google Maps API
• GitHub Docs

We have also used Google Colaboratory to quicken model training and/or evaluation.

Resources#

Academic research#

• Predicting the Resale Price of HDB Flats in Singapore (final project for CS5228 20/21 Sem 2):
  • https://www.kaggle.com/misterkix/prediction-of-singapore-hdb-price-machine-learning
  • https://xiongkexin.github.io/assets/report3.pdf
• Accuracy of Automated Valuation Model for HDB Resale Flats - https://scholarbank.nus.edu.sg/handle/10635/191601?mode=full
• Housing Price Prediction via Improved Machine Learning Techniques - https://www.sciencedirect.com/science/article/pii/S1877050920316318

Online resources#

• Towards Data Science (TDS) Medium articles:

  • Predict the Selling Price of HDB Resale Flats (TDS) - https://towardsdatascience.com/predict-the-selling-price-of-hdb-resale-flats-50530391a845
  • Predicting HDB Housing Prices using Neural Networks (TDS) - https://towardsdatascience.com/predicting-hdb-housing-prices-using-neural-networks-94ab708cccf8
  • Using Scikit-learn’s Binary Trees to Efficiently Find Latitude and Longitude Neighbors (TDS) - https://towardsdatascience.com/using-scikit-learns-binary-trees-to-efficiently-find-latitude-and-longitude-neighbors-909979bd929b
  • Choosing a scikit-learn estimator (TDS) - https://towardsdatascience.com/choosing-a-scikit-learn-linear-regression-algorithm-dd96b48105f5

• StackOverflow (SO) Q&As:

  • How to plot a map with time-slider and zoom on a city with plotly in python (SO) - https://stackoverflow.com/questions/70979065/how-to-plot-a-map-with-time-slider-and-zoom-on-a-city-with-plotly-in-python
  • How to change the colorbar range in plotly express graph (SO) - https://stackoverflow.com/questions/57383651/how-to-change-the-colorbar-range-in-plotly-express-graph
  • Pandas - Number of Months Between Two Dates (SO) - https://stackoverflow.com/questions/42822768/pandas-number-of-months-between-two-dates
  • Annotate data points while plotting from Pandas DataFrame (SO) - https://stackoverflow.com/questions/15910019/annotate-data-points-while-plotting-from-pandas-dataframe

• Bala’s Curve - https://stackedhomes.com/editorial/freehold-vs-leasehold-part-1/#gs.hbakzn

• London Relativity - https://www.graphsofrelativity.co.uk/
• How to calculate relativity - https://www.savills.com/research_articles/255800/203902-0
• Why price per sqm? - https://codyshirk.com/price-per-square-meter-m2-how-we-find-deep-value/
• Geocoding addresses - https://www.andrewbreeson.com/projects/geocoding-every-hdb
• How to Predict HDB Resale Prices using 3 different ML Models (Linear Regression, Neural Networks, k-NN) - https://royleekiat.com/2020/10/22/how-to-predict-hdb-resale-prices-using-3-different-machine-learning-models-linear-regression-neural-networks-k-nearest-neighbours/

Datasets#

The datasets that we have used are listed below:

• HDB resale flat prices dataset
• MAS core inflation measure (CPI) dataset
• Singapore overnight rate average (SORA) dataset

Video materials#

• Bagging and boosting
  • https://www.geeksforgeeks.org/xgboost/
  • https://www.researchgate.net/figure/A-general-architecture-of-XGBoost_fig3_335483097
• kNN regression
  • https://towardsdatascience.com/the-basics-knn-for-classification-and-regression-c1e8a6c955
• Regression vs classification
  • https://www.simplilearn.com/regression-vs-classification-in-machine-learning-article
• Linear vs polynomial regression
  • https://serokell.io/blog/polynomial-regression-analysis
• Property valuation
  • https://pinnacle.sg/property-valuation
• Feature engineering
  • https://medium.com/@c.giancaterino/relevance-of-feature-engineering-to-build-a-predictive-model-4c9e3e115c90
• Mean absolute percentage error (MAPE)
  • https://www.dataquest.io/blog/understanding-regression-error-metrics/
• Gradient descent
  • https://easyai.tech/en/ai-definition/gradient-descent/
• MAS
  • https://www.mas.gov.sg/

Video music#

• Hazy - Cosmos:
  • https://soundcloud.com/hazy_music/cosmos-1
• Hazy - Courage:
  • https://soundcloud.com/hazy_music/courage-album-preview
• Hazy - Universe:
  • https://soundcloud.com/hazy_music/universe

Special mentions#

We would like to thank Prof. Kan Min-Yen and Prof. Brian Lim for their teaching in this module, as well as our project mentor, Tian Xiao, for his advice to us during the course of this project.