FateMurphy/CEEMDAN_LSTM
CEEMDAN_LSTM is a Python project for decomposition-integration forecasting models based on EMD methods and LSTM.
This project helps financial analysts, traders, or operations managers forecast future trends in time-series data like stock prices or energy consumption. You input historical data, and it outputs predictions for upcoming periods. It's designed for users who need to predict future values and understand underlying patterns within complex data.
292 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to predict future values from time-series data and want to leverage advanced decomposition and deep learning techniques without building the models from scratch.
Not ideal if your data is not time-series based, or if you need to predict multiple independent variables simultaneously.
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292
Forks
49
Language
Jupyter Notebook
License
MIT
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Last pushed
Mar 03, 2025
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