This project focuses on forecasting future values of a time series dataset using the ARIMA model. It includes scripts for training the model and making predictions.
time-series/
│
├── data/ # Data files
│
└── time_series.csv # Example time series dataset
├──src/
│
├── model.py # Model definition
│
├── train.py # Training script
│
├── predict.py # Prediction script
│
└── utils.py # Utility functions
├──tests/ # Test scripts
│
└── test_model.py # Unit tests for the model
├── requirements.txt # Dependencies
└── README.md # Project documentation
- Clone the repository:
git clone https://github.com/yourusername/time-series.git cd time-series - Install the required packages: pip install -r requirements.txt
- Prepare your time series data in the /data directory and name it time_series.csv.
- Train the model: python src/train.py
- Make forecasts: python src/predict.py
Run the unit tests to ensure everything is functioning properly: python -m unittest discover -s tests
This project is licensed under the MIT License.