at-tan/Forecasting_Air_Pollution
Stacking a machine learning ensemble for multivariate time series forecasting, with the goal of predicting the one-period ahead PM 2.5 air pollution level, as published in Towards Data Science on Medium.com
ArchivedImplements a diverse base-learner stack (linear, tree-based, SVM, and neural network models) with OLS meta-learner on the Beijing air pollution dataset, addressing missing values and complex seasonalities through careful temporal splitting and forward-chain cross-validation. Achieves 5-6% improvement over persistence baseline on MAE/RMSE metrics, with the ensemble consistently outperforming individual base models across multivariate PM 2.5 prediction tasks.
Stars
43
Forks
12
Language
Jupyter Notebook
License
—
Category
Last pushed
Oct 30, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/at-tan/Forecasting_Air_Pollution"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ICCC-Platform/Air-Pollution-Image-Dataset-From-India-and-Nepal
Air Pollution Image Dataset from India and Nepal
fablabbcn/smartcitizen-data
A python package for analyzing environmental sensor's data
SIU-Sirocco-2025/Eco-Track
Giải Pháp Theo Dõi và Dự Báo Chất Lượng Không Khí TP.HCM Ứng Dụng Công Nghệ Số
Semillero-Inteligencia-Artificial-EAFIT/airedellin
Canairio sensors visualizer and predictor
nqbinhcs/AI4VN2022-Air-Quality-Forecasting-Challenge
Runner-up team (2nd place) in AI4VN2022: Air Quality Forcasting Challenge