CEEMDAN-LSTM-GradientBoosting
A state-of-the-art time series forecasting model combining CEEMDAN decomposition, LSTM neural networks, and Gradient Boosting.
Installation
You can install the package using pip:
pip install ceemdan_seglstm_gradient_boost
Usage
Here's a basic example of how to use the package:
from ceemdan_seglstm_gradient_boost import Model, Dataset_ETT_hour
# Load your data
dataset = Dataset_ETT_hour(root_path='path/to/data', flag='train', size=[12, 12, 12],
features='M', data_path='your_data.csv',
target='your_target_column', max_imfs=8)
# Initialize the model
model = Model(your_config)
# Train the model
# ... (add training code here)
# Make predictions
# ... (add prediction code here)
Dependencies
- torch
- numpy
- pandas
- matplotlib
- scikit-learn
- joblib
- PyEMD
License
This project is licensed under the MIT License.
1 maintainer
Metadata
1 maintainer
Release files for ceemdan-seglstm-gradient-boost 0.1.0
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