HDB_Resale_Prices
Predicted and identified the drivers of Singapore HDB resale prices (2015-2019) with 0.96 Rsquare & $20,000 MAE. Web app deployment using Streamlit for user price prediction. (by teyang-lau)
decision-forests
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras. (by tensorflow)
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| HDB_Resale_Prices | decision-forests | |
|---|---|---|
| 1 | 1 | |
| 21 | 650 | |
| - | 1.5% | |
| 5.4 | 8.3 | |
| 4 months ago | 4 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
HDB_Resale_Prices
Posts with mentions or reviews of HDB_Resale_Prices.
We have used some of these posts to build our list of alternatives
and similar projects.
-
What's that HDB worth?
Just curious, have you seen the projects (e.g. this) using statistical learning to predict HDB resale prices?
decision-forests
Posts with mentions or reviews of decision-forests.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-03.
-
Why do tree-based models still outperform deep learning on tabular data?
I can't explain it, but I help maintain TensorFlow Decision Forests [1] and Yggdrasil Decision Forests [2], and in an AutoML system at work that trains models on lots of various users data, decision forest models gets selected as best (after AutoML tries various model types and hyperparameters) somewhere between 20% to 40% of the times, systematically. It's pretty interesting. Other ML types considered are NN, linear models (with auto feature crossings generation), and a couple of other variations.
[1] https://github.com/tensorflow/decision-forests
What are some alternatives?
When comparing HDB_Resale_Prices and decision-forests you can also consider the following projects:
Spearmint - Spearmint Bayesian optimization codebase
yggdrasil-decision-forests - A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
srbench - A living benchmark framework for symbolic regression
higgs-logistic-regression