nredell/forecastML
An R package with Python support for multi-step-ahead forecasting with machine learning and deep learning algorithms
This tool helps data analysts and business forecasters predict future outcomes for one or more related time series using machine learning. You provide your historical time-series data, and it outputs multi-step-ahead forecasts along with their accuracy and stability assessments. It's designed for anyone needing to make predictions for business operations, resource planning, or market analysis.
131 stars. No commits in the last 6 months.
Use this if you need to create accurate, multi-step-ahead forecasts using machine learning models and want to easily evaluate their performance across different time horizons.
Not ideal if you prefer traditional, time series-specific statistical models (like ARIMA) and are not interested in using general machine learning algorithms for forecasting.
Stars
131
Forks
23
Language
R
License
—
Category
Last pushed
Jun 11, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/nredell/forecastML"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
aeon-toolkit/aeon
A toolkit for time series machine learning and deep learning
sktime/sktime
A unified framework for machine learning with time series
Nixtla/neuralforecast
Scalable and user friendly neural :brain: forecasting algorithms.
tslearn-team/tslearn
The machine learning toolkit for time series analysis in Python
Nixtla/statsforecast
Lightning ⚡️ fast forecasting with statistical and econometric models.